diff --git a/404.html b/404.html index 57d6739..1860b29 100644 --- a/404.html +++ b/404.html @@ -19,7 +19,7 @@ - +
- +
@@ -113,16 +113,16 @@

Page not found (404)

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/articles/VIM.html b/articles/VIM.html index 91534eb..edf9b2e 100644 --- a/articles/VIM.html +++ b/articles/VIM.html @@ -13,14 +13,13 @@ - - +
- +
@@ -94,7 +93,7 @@

VIM

- Source: vignettes/VIM.Rmd + Source: vignettes/VIM.Rmd
@@ -143,11 +142,7 @@

Impute missing valuesdata.frame and return another data.frame where missings are replaced by imputed values.

-x_imputed <- kNN(x)
-#> Sleep Sleep 
-#>   2.6  19.9 
-#> Dream Dream 
-#>   0.0   6.6
+x_imputed <- kNN(x)

To learn more about all implemented imputation methods, three vignettes are available

+
@@ -208,16 +201,16 @@

Visualize imputed values

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/articles/VisualImp.html b/articles/VisualImp.html index 35cd6c6..18b5ddf 100644 --- a/articles/VisualImp.html +++ b/articles/VisualImp.html @@ -13,14 +13,13 @@ - - +
- +
@@ -96,7 +95,7 @@

Wolfgang Rannetbauer

- Source: vignettes/VisualImp.Rmd + Source: vignettes/VisualImp.Rmd
@@ -125,13 +124,7 @@

Data dataset <- sleep[, c("Dream", "NonD", "BodyWgt", "Span")] # dataset with missings dataset$BodyWgt <- log(dataset$BodyWgt) dataset$Span <- log(dataset$Span) -imp_knn <- kNN(dataset) # dataset with imputed values -#> NonD BodyWgt Span NonD BodyWgt Span -#> 2.1000000 -5.2983174 0.6931472 17.9000000 8.8029735 4.6051702 -#> Dream BodyWgt Span Dream BodyWgt Span -#> 0.0000000 -5.2983174 0.6931472 6.6000000 8.8029735 4.6051702 -#> Dream NonD BodyWgt Dream NonD BodyWgt -#> 0.000000 2.100000 -5.298317 6.600000 17.900000 8.802973

+imp_knn <- kNN(dataset) # dataset with imputed values

To keep things as simple as possible, the plotting functions in VIM uses three main colors. Each color represents a property:

@@ -184,9 +177,8 @@

Function barMiss()
 # for imputed values
 x_IMPUTED <- regressionImp(NonD ~ Sleep, data = x)
-#> There still missing values in variable NonD . Probably due to missing values in the regressors.
-
-barMiss(x_IMPUTED, delimiter = "_imp", only.miss = FALSE)
+#> There still missing values in variable NonD . Probably due to missing values in the regressors. +barMiss(x_IMPUTED, delimiter = "_imp", only.miss = FALSE)

The plot indicates that there are still some missings in NonD. This is because the regression model could not be applied to observations, where @@ -208,17 +200,16 @@

Function scattMiss()scattMiss(). The following plots makes it easy to indentify missing/imputed values.

-
+
 dataset <- sleep[, c("Span", "NonD","Sleep")]
 # for missing values
 scattMiss(dataset[,-3])

 

-
+
 # for imputed values
 imp_regression <- regressionImp(NonD ~ Sleep, dataset)
-#> There still missing values in variable NonD . Probably due to missing values in the regressors.

-
-scattMiss(imp_regression[,-3], delimiter = "_imp")

+#> There still missing values in variable NonD . Probably due to missing values in the regressors.
+scattMiss(imp_regression[,-3], delimiter = "_imp")

 

 
The plot indicates that there are still some missings in
 NonD. This is because the regression model could not be
@@ -237,18 +228,17 @@ 
Function histMiss()
+
 
 ## for missing values
 x <- sleep[, c("Span", "NonD","Sleep")]
 histMiss(x, only.miss = FALSE)

 

-
+
 # for imputed values
 x_IMPUTED  <- regressionImp(NonD ~ Sleep, data = x)
-#> There still missing values in variable NonD . Probably due to missing values in the regressors.

-
-histMiss(x_IMPUTED, delimiter = "_imp", only.miss = FALSE)

+#> There still missing values in variable NonD . Probably due to missing values in the regressors.
+histMiss(x_IMPUTED, delimiter = "_imp", only.miss = FALSE)
@@ -258,19 +248,18 @@

Function matrixplot()
+
 x <- sleep[, c("Dream", "NonD","Sleep", "BodyWgt")]
 x$BodyWgt <- log(x$BodyWgt)
 # for missing values
 matrixplot(x, sortby="BodyWgt")

 

-
+
 # for imputed values - multiple variable imputation with regrssionImp()
 x_IMPUTED  <- regressionImp(NonD + Dream ~ Sleep, data = x)
 #> There still missing values in variable NonD . Probably due to missing values in the regressors.
-#> There still missing values in variable Dream . Probably due to missing values in the regressors.

-
-matrixplot(x_IMPUTED, delimiter = "_imp", sortby = "BodyWgt")

+#> There still missing values in variable Dream . Probably due to missing values in the regressors.
+matrixplot(x_IMPUTED, delimiter = "_imp", sortby = "BodyWgt")

@@ -287,18 +276,15 @@

Function marginplot()
+
 dataset <- sleep[, c("Dream", "NonD", "BodyWgt", "Span")]
 dataset$BodyWgt <- log(dataset$BodyWgt)
 dataset$Span <- log(dataset$Span)
 imp_knn <- kNN(dataset, variable = "NonD") 
-#>      Dream    BodyWgt       Span      Dream    BodyWgt       Span 
-#>  0.0000000 -5.2983174  0.6931472  6.6000000  8.8029735  4.6051702

-
-dataset[, c("NonD", "Span")] |> 
+dataset[, c("NonD", "Span")] |> 
   marginplot()

 

-
+
 imp_knn[, c("NonD", "Span", "NonD_imp")] |> 
   marginplot(delimiter = "_imp")

 

@@ -309,22 +295,17 @@ 
Function marginmatrix()The marginmatrix() function creates a scatterplot matrix
 with information about missing/imputed values in the plot margins of
 each panel.

-
+
 ## for missing values
 x <- sleep[, 2:4]
 x[, 1] <- log10(x[, 1])
 marginmatrix(x)

 

-
+
 
 ## for imputed values
 x_imp <- irmi(sleep[, 2:4])
-#> BrainWgt    Dream BrainWgt    Dream 
-#>     0.14     0.00  5712.00     6.60 
-#> BrainWgt     NonD BrainWgt     NonD 
-#>     0.14     2.10  5712.00    17.90

-
-x_imp[,1] <- log10(x_imp[, 1])
+x_imp[,1] <- log10(x_imp[, 1])
 marginmatrix(x_imp, delimiter = "_imp")

 

 

@@ -332,9 +313,7 @@ 
Function marginmatrix()
 
-        
-

+

@@ -347,16 +326,16 @@

Function marginmatrix()

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/articles/donorImp.html b/articles/donorImp.html index ce2d373..65c0def 100644 --- a/articles/donorImp.html +++ b/articles/donorImp.html @@ -13,14 +13,13 @@ - - +
- -
+ +
@@ -98,7 +97,7 @@

Wolfgang Rannetbauer

- Source: vignettes/donorImp.Rmd + Source: vignettes/donorImp.Rmd
@@ -152,10 +151,7 @@

Imputation
 imp_hotdeck <- hotdeck(dataset, variable = "NonD")  # hotdeck imputation
 imp_knn <- kNN(dataset, variable = "NonD") # kNN imputation
-#>      Dream    BodyWgt       Span      Dream    BodyWgt       Span 
-#>  0.0000000 -5.2983174  0.6931472  6.6000000  8.8029735  4.6051702

-
-imp_match <- matchImpute(dataset, variable = "NonD", match_var = c("BodyWgt","Span")) # match imputation
+imp_match <- matchImpute(dataset, variable = "NonD", match_var = c("BodyWgt","Span")) # match imputation
 aggr(imp_knn, delimiter = "_imp")
 aggr(imp_match, delimiter = "_imp")

@@ -172,17 +168,17 @@

Diagnosing the resultshotdeck(). kNN() reveals the typically procedure of methods, which are based on similar data points weighted by the distance.

-
+
 imp_hotdeck[, c("NonD", "Span", "NonD_imp")] |> 
   marginplot(delimiter = "_imp")

 

-
+
 imp_knn[, c("NonD", "Span", "NonD_imp")] |> 
   marginplot(delimiter = "_imp")

 

 
matchImpute() works by sampling values from the suitable
 donors and also provides reasonable results.

-
+
 imp_match[, c("NonD", "Span", "NonD_imp")] |> 
   marginplot(delimiter = "_imp")

 

@@ -195,7 +191,7 @@ 
Performance of methodiris dataset is used. Firstly, some values are randomly set
 to NA.

-
+
 data(iris)
 df <- iris
 colnames(df) <- c("S.Length","S.Width","P.Length","P.Width","Species")
@@ -209,26 +205,15 @@ 
Performance of method
 aggr(df)

 

-
+
 sapply(df, function(x) sum(is.na(x)))
 #> S.Length  S.Width P.Length  P.Width  Species 
 #>       10        9        8       10       12

 
We can see that there are missings in all variables and some
 observations reveal missing values on several points.

-
+
 imp_knn <- kNN(df)
-#>  S.Width P.Length  P.Width  S.Width P.Length  P.Width 
-#>      2.0      1.0      0.1      4.4      6.9      2.5 
-#> S.Length P.Length  P.Width S.Length P.Length  P.Width 
-#>      4.3      1.0      0.1      7.9      6.9      2.5 
-#> S.Length  S.Width  P.Width S.Length  S.Width  P.Width 
-#>      4.3      2.0      0.1      7.9      4.4      2.5 
-#> S.Length  S.Width P.Length S.Length  S.Width P.Length 
-#>      4.3      2.0      1.0      7.9      4.4      6.9 
-#> S.Length  S.Width P.Length  P.Width S.Length  S.Width P.Length  P.Width 
-#>      4.3      2.0      1.0      0.1      7.9      4.4      6.9      2.5

-
-aggr(imp_knn, delimiter = "imp")

+aggr(imp_knn, delimiter = "imp")

 

 
The plot indicates that all missing values have been imputed by
 kNN(). The following table displays the rounded first five
@@ -240,9 +225,7 @@ 
Performance of method
 
-        
-

+      

 
 

 
@@ -255,16 +238,16 @@ 
Performance of method
   

-
Site built with pkgdown 2.0.9.

+
Site built with pkgdown 2.1.0.
- - + + diff --git a/articles/donorImp_files/reactwidget-2.0.0/react-tools.umd.cjs b/articles/donorImp_files/reactwidget-2.0.0/react-tools.umd.cjs new file mode 100644 index 0000000..159c7ab --- /dev/null +++ b/articles/donorImp_files/reactwidget-2.0.0/react-tools.umd.cjs @@ -0,0 +1 @@ +(function(s,u){typeof exports=="object"&&typeof module<"u"?u(exports):typeof define=="function"&&define.amd?define(["exports"],u):(s=typeof globalThis<"u"?globalThis:s||self,u(s.reactR={}))})(this,function(s){"use strict";function u(n,t){if(typeof t=="string")return t;if(t.name[0]===t.name[0].toUpperCase()&&!n.hasOwnProperty(t.name))throw new Error("Unknown component: "+t.name);for(let i in t.attribs)g(t.attribs[i])&&(t.attribs[i]=u(n,t.attribs[i]));for(var a=n.hasOwnProperty(t.name)?n[t.name]:t.name,r=[a,t.attribs],e=0;e - +

- +
@@ -92,15 +92,15 @@

All vignettes

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/articles/irmi.html b/articles/irmi.html index 53a47ed..1e6ba46 100644 --- a/articles/irmi.html +++ b/articles/irmi.html @@ -13,14 +13,13 @@ - - +
- -
+ +
@@ -98,7 +97,7 @@

Wolfgang Rannetbauer

- Source: vignettes/irmi.Rmd + Source: vignettes/irmi.Rmd
@@ -155,14 +154,7 @@

Imputing multiple variables
 imp_irmi <- irmi(dataset)
-#>       NonD    BodyWgt       Span       NonD    BodyWgt       Span 
-#>  2.1000000 -5.2983174  0.6931472 17.9000000  8.8029735  4.6051702 
-#>      Dream    BodyWgt       Span      Dream    BodyWgt       Span 
-#>  0.0000000 -5.2983174  0.6931472  6.6000000  8.8029735  4.6051702 
-#>     Dream      NonD   BodyWgt     Dream      NonD   BodyWgt 
-#>  0.000000  2.100000 -5.298317  6.600000 17.900000  8.802973

-
-aggr(imp_irmi, delimiter = "_imp")
+aggr(imp_irmi, delimiter = "_imp")

We can see that irmi() imputed all missing values for all variables in our dataset.

@@ -173,13 +165,13 @@

Diagnosing the resultsNonD Bodygt plays an important role. The original data structure of NonD and BodyWgt is preserved by the irmi() imputation method.

-
+
 imp_irmi[, c("NonD", "BodyWgt", "NonD_imp")] |> 
   marginplot(delimiter = "_imp")

 

 
The same is true for the data structure of Span and
 BodyWgt.

-
+
 imp_irmi[, c("Span", "BodyWgt", "Span_imp")] |> 
   marginplot(delimiter = "_imp")

 

@@ -192,7 +184,7 @@ 
Performance of methodiris dataset is used. Firstly, some values are randomly set
 to NA.

-
+
 data(iris)
 df <- iris
 colnames(df) <- c("S.Length", "S.Width", "P.Length", "P.Width", "Species")
@@ -206,26 +198,15 @@ 
Performance of method
 aggr(df)

 

-
+
 sapply(df, function(x) sum(is.na(x)))
 #> S.Length  S.Width P.Length  P.Width  Species 
 #>       10        9        8       10       12

 
We can see that there are missings in all variables and some
 observations reveal missing values on several points.

-
+
 imp_irmi <- irmi(df)
-#>  S.Width P.Length  P.Width  S.Width P.Length  P.Width 
-#>      2.0      1.0      0.1      4.4      6.9      2.5 
-#> S.Length P.Length  P.Width S.Length P.Length  P.Width 
-#>      4.3      1.0      0.1      7.9      6.9      2.5 
-#> S.Length  S.Width  P.Width S.Length  S.Width  P.Width 
-#>      4.3      2.0      0.1      7.9      4.4      2.5 
-#> S.Length  S.Width P.Length S.Length  S.Width P.Length 
-#>      4.3      2.0      1.0      7.9      4.4      6.9 
-#> S.Length  S.Width P.Length  P.Width S.Length  S.Width P.Length  P.Width 
-#>      4.3      2.0      1.0      0.1      7.9      4.4      6.9      2.5

-
-aggr(imp_irmi, delimiter = "imp")

+aggr(imp_irmi, delimiter = "imp")

 

 
The plot indicates that all missing values have been imputed by the
 IRMI algorithm. The following table displays the rounded first five
@@ -237,9 +218,7 @@ 
Performance of method
 
-        
-

+      

 
 

 
@@ -252,16 +231,16 @@ 
Performance of method
   

-
Site built with pkgdown 2.0.9.

+
Site built with pkgdown 2.1.0.
- - + + diff --git a/articles/irmi_files/reactwidget-2.0.0/react-tools.umd.cjs b/articles/irmi_files/reactwidget-2.0.0/react-tools.umd.cjs new file mode 100644 index 0000000..159c7ab --- /dev/null +++ b/articles/irmi_files/reactwidget-2.0.0/react-tools.umd.cjs @@ -0,0 +1 @@ +(function(s,u){typeof exports=="object"&&typeof module<"u"?u(exports):typeof define=="function"&&define.amd?define(["exports"],u):(s=typeof globalThis<"u"?globalThis:s||self,u(s.reactR={}))})(this,function(s){"use strict";function u(n,t){if(typeof t=="string")return t;if(t.name[0]===t.name[0].toUpperCase()&&!n.hasOwnProperty(t.name))throw new Error("Unknown component: "+t.name);for(let i in t.attribs)g(t.attribs[i])&&(t.attribs[i]=u(n,t.attribs[i]));for(var a=n.hasOwnProperty(t.name)?n[t.name]:t.name,r=[a,t.attribs],e=0;e - - +
- -
+ +
@@ -98,7 +97,7 @@

Gregor de Cillia

- Source: vignettes/modelImp.Rmd + Source: vignettes/modelImp.Rmd
@@ -139,9 +138,8 @@

Imputation
 imp_regression <- regressionImp(NonD ~ BodyWgt + Span, dataset)
-#> There still missing values in variable NonD . Probably due to missing values in the regressors.

-
-imp_ranger <- rangerImpute(NonD ~ BodyWgt + Span, dataset)
+#> There still missing values in variable NonD . Probably due to missing values in the regressors.
+imp_ranger <- rangerImpute(NonD ~ BodyWgt + Span, dataset)
 aggr(imp_regression, delimiter = "_imp")

We can see that for regrssionImp() there are still @@ -158,17 +156,17 @@

Diagnosing the resultsregressionImp() all imputed values almost follow a straight line. This suggests that the variable Span had little to no effect on the model.

-
+
 imp_regression[, c("NonD", "BodyWgt", "NonD_imp")] |> 
   marginplot(delimiter = "_imp")

 

 
For rangerImpute() on the other hand, Span
 played an important role in the generation of the imputed values.

-
+
 imp_ranger[, c("NonD", "BodyWgt", "NonD_imp")] |> 
   marginplot(delimiter = "_imp")

 

-
+
 imp_ranger[, c("NonD", "Span", "NonD_imp")] |> 
   marginplot(delimiter = "_imp")

 

@@ -179,12 +177,11 @@ 
Imputing multiple variablesrangerImpute() and regressionImp() can be
 specified with more than one column name in the left hand side.

-
+
 imp_regression <- regressionImp(Dream + NonD ~ BodyWgt + Span, dataset)
 #> There still missing values in variable Dream . Probably due to missing values in the regressors.
-#> There still missing values in variable NonD . Probably due to missing values in the regressors.

-
-imp_ranger <- rangerImpute(Dream + NonD ~ BodyWgt + Span, dataset)
+#> There still missing values in variable NonD . Probably due to missing values in the regressors.
+imp_ranger <- rangerImpute(Dream + NonD ~ BodyWgt + Span, dataset)
 aggr(imp_regression, delimiter = "_imp")

 

 
Again, there are missings left for both Dream and
@@ -196,7 +193,7 @@ 
Performance of methodIn order to validate the performance of regressionImp()
 the iris dataset is used. Firstly, some values are randomly
 set to NA.

-
+
 library(reactable)
 
 data(iris)
@@ -212,7 +209,7 @@ 
Performance of method
 aggr(df)

 

-
+
 sapply(df, function(x)sum(is.na(x)))
 #> S.Length  S.Width P.Length  P.Width  Species 
 #>       12       10       13       12        0

@@ -220,7 +217,7 @@ 
Performance of methodSpecies
 serves as a regressor.

-
+
 imp_regression <- regressionImp(S.Length + S.Width + P.Length + P.Width ~ Species, df)
 aggr(imp_regression, delimiter = "imp")

 

@@ -234,9 +231,7 @@ 
Performance of method
 
-        
-

+      

 
 

 
@@ -249,16 +244,16 @@ 
Performance of method
   

-
Site built with pkgdown 2.0.9.

+
Site built with pkgdown 2.1.0.

 

 
       
 

 
-  
 
 
-  
+
+
 
   
 
diff --git a/articles/modelImp_files/reactwidget-2.0.0/react-tools.umd.cjs b/articles/modelImp_files/reactwidget-2.0.0/react-tools.umd.cjs
new file mode 100644
index 0000000..159c7ab
--- /dev/null
+++ b/articles/modelImp_files/reactwidget-2.0.0/react-tools.umd.cjs
@@ -0,0 +1 @@
+(function(s,u){typeof exports=="object"&&typeof module<"u"?u(exports):typeof define=="function"&&define.amd?define(["exports"],u):(s=typeof globalThis<"u"?globalThis:s||self,u(s.reactR={}))})(this,function(s){"use strict";function u(n,t){if(typeof t=="string")return t;if(t.name[0]===t.name[0].toUpperCase()&&!n.hasOwnProperty(t.name))throw new Error("Unknown component: "+t.name);for(let i in t.attribs)g(t.attribs[i])&&(t.attribs[i]=u(n,t.attribs[i]));for(var a=n.hasOwnProperty(t.name)?n[t.name]:t.name,r=[a,t.attribs],e=0;e
 
 
-    
+
 
     

       

   

 

 
-      
+
 
       

   

@@ -69,9 +69,9 @@
         
Authors and Citation

       

 
-      
+
       
  • 
-          
    Matthias Templ. Author, maintainer. 
+          
    Matthias Templ. Author, maintainer.
           
    
         
    • 
         
  • 
@@ -79,26 +79,26 @@ 
    Authors and Citation
    
           
    
         
    • 
         
  • 
-          
    Andreas Alfons. Author. 
+          
    Andreas Alfons. Author.
           
    
         
    • 
         
  • 
-          
    Gregor de Cillia. Author. 
+          
    Gregor de Cillia. Author.
           
    
         
    • 
         
  • 
-          
    Bernd Prantner. Contributor. 
+          
    Bernd Prantner. Contributor.
           
    
         
    • 
         
  • 
-          
    Wolfgang Rannetbauer. Author. 
+          
    Wolfgang Rannetbauer. Author.
           
    
         
    • 
       

     

     

       
Citation

-      Source: inst/CITATION
+      Source: inst/CITATION
     

     

 
@@ -126,15 +126,15 @@ 
Citation
-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/index.html b/index.html index 5ff0c73..b6a9d53 100644 --- a/index.html +++ b/index.html @@ -20,7 +20,7 @@ - +
- +
@@ -187,16 +187,16 @@

Developers

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/news/index.html b/news/index.html index da1b649..cb1df0c 100644 --- a/news/index.html +++ b/news/index.html @@ -3,7 +3,7 @@ - +
- +

Changelog

- Source: NEWS.md + Source: NEWS.md
@@ -245,15 +245,15 @@

VIM 4.0.02013-

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/pkgdown.yml b/pkgdown.yml index 298c165..3e00d5a 100644 --- a/pkgdown.yml +++ b/pkgdown.yml @@ -1,5 +1,5 @@ pandoc: 3.1.11 -pkgdown: 2.0.9 +pkgdown: 2.1.0 pkgdown_sha: ~ articles: donorImp: donorImp.html @@ -7,5 +7,4 @@ articles: modelImp: modelImp.html VIM: VIM.html VisualImp: VisualImp.html -last_built: 2024-06-13T14:52Z - +last_built: 2024-07-15T09:48Z diff --git a/reference/Animals_na.html b/reference/Animals_na.html index fb64c3b..ec926a8 100644 --- a/reference/Animals_na.html +++ b/reference/Animals_na.html @@ -3,7 +3,7 @@ - +
- +

Animals_na

- Source: R/VIM-package.R + Source: R/VIM-package.R
@@ -121,15 +121,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/SBS5242.html b/reference/SBS5242.html index 1f38f2d..86020ad 100644 --- a/reference/SBS5242.html +++ b/reference/SBS5242.html @@ -4,7 +4,7 @@ - +
- +

Synthetic subset of the Austrian structural business statistics data

- Source: R/VIM-package.R + Source: R/VIM-package.R
@@ -112,15 +112,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/VIM-package.html b/reference/VIM-package.html index 7db7b14..e243e61 100644 --- a/reference/VIM-package.html +++ b/reference/VIM-package.html @@ -10,7 +10,7 @@ - +
- +

Visualization and Imputation of Missing Values

- Source: R/VIM-package.R + Source: R/VIM-package.R
@@ -129,15 +129,15 @@

Author

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/aggr.html b/reference/aggr.html index 7da4c12..31a489b 100644 --- a/reference/aggr.html +++ b/reference/aggr.html @@ -7,7 +7,7 @@ - +
- +

Aggregations for missing/imputed values

- Source: R/aggr.R + Source: R/aggr.R
@@ -85,7 +85,7 @@

Aggregations for missing/imputed values

aggr(x, delimiter = NULL, plot = TRUE, ...)
 
-# S3 method for aggr
+# S3 method for class 'aggr'
 plot(
   x,
   col = c("skyblue", "red", "orange"),
@@ -108,23 +108,25 @@ 
Aggregations for missing/imputed values

   ...
 )
 
-# S3 method for aggr
+# S3 method for class 'aggr'
 print(x, ..., digits = NULL)
 
-# S3 method for aggr
+# S3 method for class 'aggr'
 summary(object, ...)
 
-# S3 method for summary.aggr
+# S3 method for class 'summary.aggr'
 print(x, ...)

Arguments

-
x
+ + +
x

an object of class "summary.aggr".

-
delimiter
+
delimiter

a character-vector to distinguish between variables and imputation-indices for imputed variables (therefore, x needs to have colnames()). If given, it is used to determine the corresponding @@ -134,16 +136,16 @@

Arguments

to the given colors for imputed variables (see col).

-
plot
+
plot

a logical indicating whether the results should be plotted (the default is TRUE).

-
...
+
...

Further arguments, currently ignored.

-
col
+
col

a vector of length three giving the colors to be used for observed, missing and imputed data. If only one color is supplied, it is used for missing and imputed data and observed data is transparent. If only @@ -151,22 +153,22 @@

Arguments

second color is used for missing and imputed data.

-
bars
+
bars

a logical indicating whether a small barplot for the frequencies of the different combinations should be drawn.

-
numbers
+
numbers

a logical indicating whether the proportion or frequencies of the different combinations should be represented by numbers.

-
prop
+
prop

a logical indicating whether the proportion of missing/imputed values and combinations should be used rather than the total amount.

-
combined
+
combined

a logical indicating whether the two plots should be combined. If FALSE, a separate barplot on the left hand side shows the amount of missing/imputed values in each variable. If TRUE, a @@ -175,12 +177,12 @@

Arguments

“Details” for more information.

-
varheight
+
varheight

a logical indicating whether the cell heights are given by the frequencies of occurrence of the corresponding combinations.

-
only.miss
+
only.miss

a logical indicating whether the small barplot for the frequencies of the combinations should only be drawn for combinations including missing/imputed values (if bars is TRUE). This is @@ -190,70 +192,68 @@

Arguments

determined by prop) is then represented by a number instead of a bar.

-
border
+
border

the color to be used for the border of the bars and rectangles. Use border=NA to omit borders.

-
sortVars
+
sortVars

a logical indicating whether the variables should be sorted by the number of missing/imputed values.

-
sortCombs
+
sortCombs

a logical indicating whether the combinations should be sorted by the frequency of occurrence.

-
ylabs
+
ylabs

if combined is TRUE, a character string giving the y-axis label of the combined plot, otherwise a character vector of length two giving the y-axis labels for the two plots.

-
axes
+
axes

a logical indicating whether axes should be drawn.

-
labels
+
labels

either a logical indicating whether labels should be plotted on the x-axis, or a character vector giving the labels.

-
cex.lab
+
cex.lab

the character expansion factor to be used for the axis labels.

-
cex.axis
+
cex.axis

the character expansion factor to be used for the axis annotation.

-
cex.numbers
+
cex.numbers

the character expansion factor to be used for the proportion or frequencies of the different combinations

-
gap
+
gap

if combined is FALSE, a numeric value giving the distance between the two plots in margin lines.

-
digits
+
digits

the minimum number of significant digits to be used (see print.default()).

-
object
+
object

an object of class "aggr".

Value

- - -

for aggr, a list of class "aggr" containing the +

for aggr, a list of class "aggr" containing the following components:

  • x the data used.

  • combinations a character vector representing the combinations of variables.

    • @@ -316,7 +316,7 @@

    See also

    aggr()

    print.summary.aggr(), aggr()

    summary.aggr(), aggr()

    -

    Other plotting functions: +

    Other plotting functions: barMiss(), histMiss(), marginmatrix(), @@ -384,36 +384,6 @@

    Examples

    ## for imputed values sleep_IMPUTED <- kNN(sleep) -#> BodyWgt BrainWgt Dream Sleep Span Gest Pred Exp -#> 0.005 0.140 0.000 2.600 2.000 12.000 1.000 1.000 -#> Danger BodyWgt BrainWgt Dream Sleep Span Gest Pred -#> 1.000 6654.000 5712.000 6.600 19.900 100.000 645.000 5.000 -#> Exp Danger -#> 5.000 5.000 -#> BodyWgt BrainWgt NonD Sleep Span Gest Pred Exp -#> 0.005 0.140 2.100 2.600 2.000 12.000 1.000 1.000 -#> Danger BodyWgt BrainWgt NonD Sleep Span Gest Pred -#> 1.000 6654.000 5712.000 17.900 19.900 100.000 645.000 5.000 -#> Exp Danger -#> 5.000 5.000 -#> BodyWgt BrainWgt NonD Dream Span Gest Pred Exp -#> 0.005 0.140 2.100 0.000 2.000 12.000 1.000 1.000 -#> Danger BodyWgt BrainWgt NonD Dream Span Gest Pred -#> 1.000 6654.000 5712.000 17.900 6.600 100.000 645.000 5.000 -#> Exp Danger -#> 5.000 5.000 -#> BodyWgt BrainWgt NonD Dream Sleep Gest Pred Exp -#> 0.005 0.140 2.100 0.000 2.600 12.000 1.000 1.000 -#> Danger BodyWgt BrainWgt NonD Dream Sleep Gest Pred -#> 1.000 6654.000 5712.000 17.900 6.600 19.900 645.000 5.000 -#> Exp Danger -#> 5.000 5.000 -#> BodyWgt BrainWgt NonD Dream Sleep Span Pred Exp -#> 0.005 0.140 2.100 0.000 2.600 2.000 1.000 1.000 -#> Danger BodyWgt BrainWgt NonD Dream Sleep Span Pred -#> 1.000 6654.000 5712.000 17.900 6.600 19.900 100.000 5.000 -#> Exp Danger -#> 5.000 5.000 a <- aggr(sleep_IMPUTED, delimiter="_imp") a @@ -535,15 +505,15 @@

    Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/alphablend.html b/reference/alphablend.html index c7dcaec..dc22ae9 100644 --- a/reference/alphablend.html +++ b/reference/alphablend.html @@ -3,7 +3,7 @@ - +
- +

Alphablending for colors

- Source: R/alphablend.R + Source: R/alphablend.R
@@ -80,15 +80,17 @@

Alphablending for colors

Arguments

-
col
+ + +
col

a vector specifying colors.

-
alpha
+
alpha

a numeric vector containing the alpha values (between 0 and 1).

-
bg
+
bg

the background color to be used for alphablending. This can be used as a workaround for graphics devices that do not support semitransparent colors.

@@ -96,9 +98,7 @@

Arguments

Value

- - -

a vector containing the semitransparent colors.

+

a vector containing the semitransparent colors.

Author

@@ -125,15 +125,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/barMiss.html b/reference/barMiss.html index c74e5de..8f34e35 100644 --- a/reference/barMiss.html +++ b/reference/barMiss.html @@ -6,7 +6,7 @@ - +
- +

Barplot with information about missing/imputed values

- Source: R/barMiss.R + Source: R/barMiss.R
@@ -103,11 +103,13 @@

Barplot with information about missing/imputed values

Arguments

-
x
+ + +
x

a vector, matrix or data.frame.

-
delimiter
+
delimiter

a character-vector to distinguish between variables and imputation-indices for imputed variables (therefore, x needs to have colnames()). If given, it is used to determine the corresponding @@ -117,12 +119,12 @@

Arguments

to the given colors for imputed variables (see col).

-
pos
+
pos

a numeric value giving the index of the variable of interest. Additional variables in x are used for highlighting.

-
selection
+
selection

the selection method for highlighting missing/imputed values in multiple additional variables. Possible values are "any" (highlighting of missing/imputed values in any of the additional @@ -130,62 +132,60 @@

Arguments

all of the additional variables).

-
col
+
col

a vector of length six giving the colors to be used. If only one color is supplied, the bars are transparent and the supplied color is used for highlighting missing/imputed values. Else if two colors are supplied, they are recycled.

-
border
+
border

the color to be used for the border of the bars. Use border=NA to omit borders.

-
main, sub
+
main, sub

main and sub title.

-
xlab, ylab
+
xlab, ylab

axis labels.

-
axes
+
axes

a logical indicating whether axes should be drawn on the plot.

-
labels
+
labels

either a logical indicating whether labels should be plotted below each bar, or a character vector giving the labels.

-
only.miss
+
only.miss

logical; if TRUE, the missing/imputed values in the variable of interest are visualized by a single bar. Otherwise, a small barplot is drawn on the right hand side (see ‘Details’).

-
miss.labels
+
miss.labels

either a logical indicating whether label(s) should be plotted below the bar(s) on the right hand side, or a character string or vector giving the label(s) (see ‘Details’).

-
interactive
+
interactive

a logical indicating whether variables can be switched interactively (see ‘Details’).

-
...
+
...

further graphical parameters to be passed to graphics::title() and graphics::axis().

Value

- - -

a numeric vector giving the coordinates of the midpoints of the +

a numeric vector giving the coordinates of the midpoints of the bars.

@@ -231,7 +231,7 @@

References

See also

spineMiss(), histMiss()

-

Other plotting functions: +

Other plotting functions: aggr(), histMiss(), marginmatrix(), @@ -265,8 +265,6 @@

Examples

## for imputed values x_IMPUTED <- kNN(sleep[, c("Exp", "Sleep")]) -#> Exp Exp -#> 1 5 barMiss(x_IMPUTED, delimiter = "_imp") barMiss(x_IMPUTED, delimiter = "_imp", only.miss = FALSE) @@ -287,15 +285,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/bcancer.html b/reference/bcancer.html index c621979..7769b0d 100644 --- a/reference/bcancer.html +++ b/reference/bcancer.html @@ -3,7 +3,7 @@ - +
- +

Breast cancer Wisconsin data set

- Source: R/VIM-package.R + Source: R/VIM-package.R
@@ -155,15 +155,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/bgmap.html b/reference/bgmap.html index 745d383..2ac2d61 100644 --- a/reference/bgmap.html +++ b/reference/bgmap.html @@ -3,7 +3,7 @@ - +
- +

Backgound map

- Source: R/bgmap.R + Source: R/bgmap.R
@@ -80,7 +80,9 @@

Backgound map

Arguments

-
map
+ + +
map

either a matrix or data.frame with two columns, a list with components x and y, or an object of any class that can be used for maps and provides its own plot method (e.g., @@ -88,12 +90,12 @@

Arguments

mentioned types can also be provided.

-
add
+
add

a logical indicating whether map should be added to an already existing plot (the default is FALSE).

-
...
+
...

further arguments and graphical parameters to be passed to plot and/or graphics::lines().

@@ -134,15 +136,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/brittleness.html b/reference/brittleness.html index 1143dbb..aca0a53 100644 --- a/reference/brittleness.html +++ b/reference/brittleness.html @@ -5,7 +5,7 @@ - +
- +

Brittleness index data set

- Source: R/VIM-package.R + Source: R/VIM-package.R
@@ -118,15 +118,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/chorizonDL.html b/reference/chorizonDL.html index 561e2ea..83e0b45 100644 --- a/reference/chorizonDL.html +++ b/reference/chorizonDL.html @@ -5,7 +5,7 @@ - +
- +

C-horizon of the Kola data with missing values

- Source: R/VIM-package.R + Source: R/VIM-package.R
@@ -359,7 +359,7 @@

Format

Ti_XRF

a numeric vector

- +

Source

@@ -621,15 +621,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/colSequence.html b/reference/colSequence.html index 343892f..5aa7450 100644 --- a/reference/colSequence.html +++ b/reference/colSequence.html @@ -5,7 +5,7 @@ - +
- +

HCL and RGB color sequences

- Source: R/colSequence.R + Source: R/colSequence.R
@@ -88,13 +88,15 @@

HCL and RGB color sequences

Arguments

-
p
+ + +
p

a numeric vector with values between 0 and 1 giving values to be used for interpolation between the start and end color (0 corresponds to the start color, 1 to the end color).

-
start, end
+
start, end

the start and end color, respectively. For HCL colors, each can be supplied as a vector of length three (hue, chroma, luminance) or an object of class "colorspace::polarLUV()". For RGB colors, @@ -102,37 +104,35 @@

Arguments

green, blue) or an object of class "colorspace::RGB()".

-
space
+
space

character string; if start and end are both numeric, this determines whether they refer to HCL or RGB values. Possible values are "hcl" (for the HCL space) or "rgb" (for the RGB space).

-
...
+
...

for colSequence, additional arguments to be passed to colSequenceHCL or colSequenceRGB. For colSequenceHCL and colSequenceRGB, additional arguments to be passed to colorspace::hex().

-
fixup
+
fixup

a logical indicating whether the colors should be corrected to valid RGB values (see colorspace::hex()).

Value

- - -

A character vector containing hexadecimal strings of the form +

A character vector containing hexadecimal strings of the form "#RRGGBB".

References

Zeileis, A., Hornik, K., Murrell, P. (2009) Escaping RGBland: Selecting colors for statistical graphics. Computational Statistics & -Data Analysis, 53 (9), 1259--1270.

+Data Analysis, 53 (9), 1259–1270.

See also

@@ -175,15 +175,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/colic.html b/reference/colic.html index aa619ff..d3a6642 100644 --- a/reference/colic.html +++ b/reference/colic.html @@ -7,7 +7,7 @@ - +
- +

Colic horse data set

- Source: R/VIM-package.R + Source: R/VIM-package.R
@@ -217,15 +217,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/collisions.html b/reference/collisions.html index 96f68f1..2c4ad10 100644 --- a/reference/collisions.html +++ b/reference/collisions.html @@ -3,7 +3,7 @@ - +
- +

Subset of the collision data

- Source: R/VIM-package.R + Source: R/VIM-package.R
@@ -105,15 +105,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/colormapMiss.html b/reference/colormapMiss.html index a24c56d..496d98f 100644 --- a/reference/colormapMiss.html +++ b/reference/colormapMiss.html @@ -6,7 +6,7 @@ - +
- +

Colored map with information about missing/imputed values

- Source: R/colormapMiss.R + Source: R/colormapMiss.R
@@ -120,44 +120,46 @@

Colored map with information about missing/imputed values

Arguments

-
x
+ + +
x

a numeric vector.

-
region
+
region

a vector or factor of the same length as x giving the regions.

-
map
+
map

an object of any class that contains polygons and provides its own plot method (e.g., "SpatialPolygons" from package sp).

-
imp_index
+
imp_index

a logical-vector indicating which values of ‘x’ have been imputed. If given, it is used for highlighting and the colors are adjusted according to the given colors for imputed variables (see col).

-
prop
+
prop

a logical indicating whether the proportion of missing/imputed values should be used rather than the total amount.

-
polysRegion
+
polysRegion

a numeric vector specifying the region that each polygon belongs to.

-
range
+
range

a numeric vector of length two specifying the range (minimum and maximum) of the proportion or amount of missing/imputed values to be used for the color scheme.

-
n
+
n

for colormapMiss, the number of equally spaced cut-off points for a discretized color scheme. If this is not a positive integer, a continuous color scheme is used (the default). In the latter case, the @@ -166,7 +168,7 @@

Arguments

continuously.

-
col
+
col

the color range (start end end) to be used. RGB colors may be specified as character strings or as objects of class "colorspace::RGB()". HCL colors need to be specified as objects @@ -175,84 +177,82 @@

Arguments

transparent for RGB or white for HCL.

-
gamma
+
gamma

numeric; the display gamma value (see colorspace::hex()).

-
fixup
+
fixup

a logical indicating whether the colors should be corrected to valid RGB values (see colorspace::hex()).

-
coords
+
coords

a matrix or data.frame with two columns giving the coordinates for the labels.

-
numbers
+
numbers

a logical indicating whether the corresponding proportions or numbers of missing/imputed values should be used as labels for the regions.

-
digits
+
digits

the number of digits to be used in the labels (in case of proportions).

-
cex.numbers
+
cex.numbers

the character expansion factor to be used for the labels.

-
col.numbers
+
col.numbers

the color to be used for the labels.

-
legend
+
legend

a logical indicating whether a legend should be plotted.

-
interactive
+
interactive

a logical indicating whether more detailed information about missing/imputed values should be displayed interactively (see ‘Details’).

-
...
+
...

further arguments to be passed to plot.

-
xleft
+
xleft

left x position of the legend.

-
ybottom
+
ybottom

bottom y position of the legend.

-
xright
+
xright

right x position of the legend.

-
ytop
+
ytop

top y position of the legend.

-
cmap
+
cmap

a list as returned by colormapMiss that contains the required information for the legend.

-
horizontal
+
horizontal

a logical indicating whether the legend should be drawn horizontally or vertically.

Value

- - -

colormapMiss returns a list with the following components:

  • nmiss a numeric vector containing the number of missing/imputed +

    colormapMiss returns a list with the following components:

    • nmiss a numeric vector containing the number of missing/imputed values in each region.

    • nobs a numeric vector containing the number of observations in each region.

      • @@ -322,15 +322,15 @@

      Author

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/countInf.html b/reference/countInf.html index 60e76b0..00162f3 100644 --- a/reference/countInf.html +++ b/reference/countInf.html @@ -3,7 +3,7 @@ - +
- +

Count number of infinite or missing values

- Source: R/utils.R + Source: R/utils.R
@@ -80,15 +80,15 @@

Count number of infinite or missing values

Arguments

-
x
+ + +
x

a vector.

Value

- - -

countInf returns the number of infinite values in x. +

countInf returns the number of infinite values in x. countNA returns the number of missing values in x.

@@ -117,15 +117,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/diabetes.html b/reference/diabetes.html index 72468c7..423a90f 100644 --- a/reference/diabetes.html +++ b/reference/diabetes.html @@ -5,7 +5,7 @@ - +
- +

Indian Prime Diabetes Data

- Source: R/VIM-package.R + Source: R/VIM-package.R
@@ -128,7 +128,7 @@

Details

References

Smith, J.W., Everhart, J.E., Dickson, W.C., Knowler, W.C., & Johannes, R.S. (1988). Using the ADAP learning algorithm to forecast the onset of diabetes mellitus. -In Proceedings of the Symposium on Computer Applications and Medical Care (pp. 261--265). IEEE Computer Society Press.

+In Proceedings of the Symposium on Computer Applications and Medical Care (pp. 261–265). IEEE Computer Society Press.

@@ -152,15 +152,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/evaluation.html b/reference/evaluation.html index 7f8aa7b..c522dbe 100644 --- a/reference/evaluation.html +++ b/reference/evaluation.html @@ -3,7 +3,7 @@ - +
- +

Error performance measures

- Source: R/evaluation.R + Source: R/evaluation.R
@@ -88,27 +88,27 @@

Error performance measures

Arguments

-
x
+ + +
x

matrix or data frame

-
y
+
y

matrix or data frame of the same size as x

-
m
+
m

the indicator matrix for missing cells

-
vartypes
+
vartypes

a vector of length ncol(x) specifying the variables types, like factor or numeric

Value

- - -

the error measures value

+

the error measures value

Details

@@ -136,14 +136,6 @@

Examples

iris_imp$Species[sample(1:nrow(iris), 10)] <- NA m <- is.na(iris_imp) iris_imp <- kNN(iris_imp, imp_var = FALSE) -#> Sepal.Width Petal.Length Petal.Width Sepal.Width Petal.Length Petal.Width -#> 2.0 1.0 0.1 4.4 6.9 2.5 -#> Sepal.Length Petal.Length Petal.Width Sepal.Length Petal.Length Petal.Width -#> 4.3 1.0 0.1 7.9 6.9 2.5 -#> Sepal.Length Sepal.Width Petal.Length Petal.Width Sepal.Length Sepal.Width -#> 4.3 2.0 1.0 0.1 7.9 4.4 -#> Petal.Length Petal.Width -#> 6.9 2.5 evaluation(iris_orig, iris_imp, m = m, vartypes = c(rep("numeric", 4), "factor")) #> $err_num #> [1] 0.149 @@ -170,15 +162,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/food.html b/reference/food.html index 7320d85..766abb1 100644 --- a/reference/food.html +++ b/reference/food.html @@ -3,7 +3,7 @@ - +
- +

Food consumption

- Source: R/VIM-package.R + Source: R/VIM-package.R
@@ -132,15 +132,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/gapMiss.html b/reference/gapMiss.html index b308014..f48f0b7 100644 --- a/reference/gapMiss.html +++ b/reference/gapMiss.html @@ -3,7 +3,7 @@ - +
- +

Missing value gap statistics

- Source: R/gapMiss.R + Source: R/gapMiss.R
@@ -80,20 +80,20 @@

Missing value gap statistics

Arguments

-
x
+ + +
x

a numeric vector

-
what
+
what

default is the arithmetic mean. One can include an own function that returns a vector of lenght 1 (e.g. median)

Value

- - -

The gap statistics

+

The gap statistics

Details

@@ -138,15 +138,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/gowerD.html b/reference/gowerD.html index c9b0fcd..d5f1ec1 100644 --- a/reference/gowerD.html +++ b/reference/gowerD.html @@ -4,7 +4,7 @@ - +
- +

Computes the extended Gower distance of two data sets

- Source: R/gowerD.R + Source: R/gowerD.R
@@ -96,55 +96,57 @@

Computes the extended Gower distance of two data sets

Arguments

-
data.x
+ + +
data.x

data frame

-
data.y
+
data.y

data frame

-
weights
+
weights

numeric vector providing weights for the observations in x

-
numerical
+
numerical

names of numerical variables

-
factors
+
factors

names of factor variables

-
orders
+
orders

names of ordered variables

-
mixed
+
mixed

names of mixed variables

-
levOrders
+
levOrders

vector with number of levels for each orders variable

-
mixed.constant
+
mixed.constant

vector with length equal to the number of semi-continuous variables specifying the point of the semi-continuous distribution with non-zero probability

-
returnIndex
+
returnIndex

logical if TRUE return the index of the minimum distance

-
nMin
+
nMin

integer number of values with smallest distance to be returned

-
returnMin
+
returnMin

logical if the computed distances for the indices should be returned

-
methodStand
+
methodStand

character either "range" or "iqr", iqr is more robust for outliers

@@ -159,12 +161,6 @@

Examples

data(sleep)
 # all variables used as numerical
 gowerD(sleep)
-#>  BodyWgt BrainWgt     NonD    Dream    Sleep     Span     Gest     Pred 
-#>    0.005    0.140    2.100    0.000    2.600    2.000   12.000    1.000 
-#>      Exp   Danger  BodyWgt BrainWgt     NonD    Dream    Sleep     Span 
-#>    1.000    1.000 6654.000 5712.000   17.900    6.600   19.900  100.000 
-#>     Gest     Pred      Exp   Danger 
-#>  645.000    5.000    5.000    5.000 
 #>            [,1]       [,2]        [,3]      [,4]      [,5]       [,6]
 #>  [1,] 0.0000000 0.80194496 0.569870867 0.6617888 0.5166715 0.73966024
 #>  [2,] 0.8019450 0.00000000 0.480629002 0.6656651 0.4565394 0.21901970
@@ -799,10 +795,6 @@ 
Examples

 # split in numerical an
 gowerD(sleep, numerical = c("BodyWgt", "BrainWgt", "NonD", "Dream", "Sleep", "Span", "Gest"),
   orders = c("Pred","Exp","Danger"), levOrders = c(5,5,5))
-#>  BodyWgt BrainWgt     NonD    Dream    Sleep     Span     Gest  BodyWgt 
-#>    0.005    0.140    2.100    0.000    2.600    2.000   12.000 6654.000 
-#> BrainWgt     NonD    Dream    Sleep     Span     Gest 
-#> 5712.000   17.900    6.600   19.900  100.000  645.000 
 #>            [,1]       [,2]        [,3]      [,4]      [,5]       [,6]
 #>  [1,] 0.0000000 0.80194496 0.569870867 0.6617888 0.5166715 0.73966024
 #>  [2,] 0.8019450 0.00000000 0.480629002 0.6656651 0.4565394 0.21901970
@@ -1437,10 +1429,6 @@ 
Examples

 # as before but only returning the index of the closest observation
 gowerD(sleep, numerical = c("BodyWgt", "BrainWgt", "NonD", "Dream", "Sleep", "Span", "Gest"),
   orders = c("Pred","Exp","Danger"), levOrders = c(5,5,5), returnIndex = TRUE)
-#>  BodyWgt BrainWgt     NonD    Dream    Sleep     Span     Gest  BodyWgt 
-#>    0.005    0.140    2.100    0.000    2.600    2.000   12.000 6654.000 
-#> BrainWgt     NonD    Dream    Sleep     Span     Gest 
-#> 5712.000   17.900    6.600   19.900  100.000  645.000 
 #> $ind
 #>      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14]
 #> [1,]    1    2    3    4    5    6    7    8    9    10    11    12    13    14
@@ -1470,15 +1458,15 @@ 
Examples
-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/growdotMiss.html b/reference/growdotMiss.html index 063e1a1..84a3325 100644 --- a/reference/growdotMiss.html +++ b/reference/growdotMiss.html @@ -5,7 +5,7 @@ - +
- +

Growing dot map with information about missing/imputed values

- Source: R/growdotMiss.R + Source: R/growdotMiss.R
@@ -107,25 +107,27 @@

Growing dot map with information about missing/imputed values

Arguments

-
x
+ + +
x

a vector, matrix or data.frame.

-
coords
+
coords

a matrix or data.frame with two columns giving the spatial coordinates of the observations.

-
map
+
map

a background map to be passed to bgmap().

-
pos
+
pos

a numeric value giving the index of the variable determining the dot sizes.

-
delimiter
+
delimiter

a character-vector to distinguish between variables and imputation-indices for imputed variables (therefore, x needs to have colnames()). If given, it is used to determine the corresponding @@ -135,7 +137,7 @@

Arguments

to the given colors for imputed variables (see col).

-
selection
+
selection

the selection method for highlighting missing/imputed values in multiple additional variables. Possible values are "any" (highlighting of missing/imputed values in any of the additional @@ -143,79 +145,79 @@

Arguments

all of the additional variables).

-
log
+
log

a logical indicating whether the variable given by pos should be log-transformed.

-
col
+
col

a vector of length six giving the colors to be used in the plot. If only one color is supplied, it is used for the borders of non-highlighted dots and the surface area of highlighted dots. Else if two colors are supplied, they are recycled.

-
border
+
border

a vector of length four giving the colors to be used for the borders of the growing dots. Use NA to omit borders.

-
alpha
+
alpha

a numeric value between 0 and 1 giving the level of transparency of the colors, or NULL. This can be used to prevent overplotting.

-
scale
+
scale

scaling factor of the map.

-
size
+
size

a vector of length two giving the sizes for the smallest and largest dots.

-
exp
+
exp

a vector of length three giving the factors that define the shape of the exponential function (see ‘Details’).

-
col.map
+
col.map

the color to be used for the background map.

-
legend
+
legend

a logical indicating whether a legend should be plotted.

-
legtitle
+
legtitle

the title for the legend.

-
cex.legtitle
+
cex.legtitle

the character expansion factor to be used for the title of the legend.

-
cex.legtext
+
cex.legtext

the character expansion factor to be used in the legend.

-
ncircles
+
ncircles

the number of circles displayed in the legend.

-
ndigits
+
ndigits

the number of digits displayed in the legend. Note that \ this is just a suggestion (see format()).

-
interactive
+
interactive

a logical indicating whether information about certain observations can be displayed interactively (see ‘Details’).

-
...
+
...

for growdotMiss, further arguments and graphical parameters to be passed to bgmap(). For bubbleMiss, the arguments to be passed to growdotMiss.

@@ -273,10 +275,6 @@

Examples

## for imputed values x_imp <- kNN(chorizonDL[,c("Ca","As","Bi" )]) -#> Ca Bi Ca Bi -#> 1.10e+02 6.00e-03 4.17e+04 3.89e+00 -#> Ca As Ca As -#> 110.0 0.1 41700.0 30.7 growdotMiss(x_imp, coo, kola.background, delimiter = "_imp", border = "white") #> @@ -298,15 +296,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/histMiss.html b/reference/histMiss.html index ec2292a..9b4ae59 100644 --- a/reference/histMiss.html +++ b/reference/histMiss.html @@ -6,7 +6,7 @@ - +
- +

Histogram with information about missing/imputed values

- Source: R/histMiss.R + Source: R/histMiss.R
@@ -104,11 +104,13 @@

Histogram with information about missing/imputed values

Arguments

-
x
+ + +
x

a vector, matrix or data.frame.

-
delimiter
+
delimiter

a character-vector to distinguish between variables and imputation-indices for imputed variables (therefore, x needs to have colnames()). If given, it is used to determine the corresponding @@ -118,12 +120,12 @@

Arguments

to the given colors for imputed variables (see col).

-
pos
+
pos

a numeric value giving the index of the variable of interest. Additional variables in x are used for highlighting.

-
selection
+
selection

the selection method for highlighting missing/imputed values in multiple additional variables. Possible values are "any" (highlighting of missing/imputed values in any of the additional @@ -131,68 +133,66 @@

Arguments

all of the additional variables).

-
breaks
+
breaks

either a character string naming an algorithm to compute the breakpoints (see hist()), or a numeric value giving the number of cells.

-
right
+
right

logical; if TRUE, the histogram cells are right-closed (left-open) intervals.

-
col
+
col

a vector of length six giving the colors to be used. If only one color is supplied, the bars are transparent and the supplied color is used for highlighting missing/imputed values. Else if two colors are supplied, they are recycled.

-
border
+
border

the color to be used for the border of the cells. Use border=NA to omit borders.

-
main, sub
+
main, sub

main and sub title.

-
xlab, ylab
+
xlab, ylab

axis labels.

-
axes
+
axes

a logical indicating whether axes should be drawn on the plot.

-
only.miss
+
only.miss

logical; if TRUE, the missing/imputed values in the first variable are visualized by a single bar. Otherwise, a small barplot is drawn on the right hand side (see ‘Details’).

-
miss.labels
+
miss.labels

either a logical indicating whether label(s) should be plotted below the bar(s) on the right hand side, or a character string or vector giving the label(s) (see ‘Details’).

-
interactive
+
interactive

a logical indicating whether the variables can be switched interactively (see ‘Details’).

-
...
+
...

further graphical parameters to be passed to graphics::title() and graphics::axis().

Value

- - -

a list with the following components:

  • breaks the breakpoints.

    • +

    a list with the following components:

    • breaks the breakpoints.

    • counts the number of observations in each cell.

    • missings the number of highlighted observations in each cell.

    • mids the cell midpoints.

      • @@ -239,7 +239,7 @@

      References

      See also

      spineMiss(), barMiss()

      -

      Other plotting functions: +

      Other plotting functions: aggr(), barMiss(), marginmatrix(), @@ -272,10 +272,6 @@

      Examples

      ## for imputed values x_IMPUTED <- kNN(tao[, c("Air.Temp", "Humidity")]) -#> Humidity Humidity -#> 71.6 94.8 -#> Air.Temp Air.Temp -#> 21.42 28.50 histMiss(x_IMPUTED, delimiter = "_imp") histMiss(x_IMPUTED, delimiter = "_imp", only.miss = FALSE) @@ -295,15 +291,15 @@

      Examples

      -

      Site built with pkgdown 2.0.9.

      +

      Site built with pkgdown 2.1.0.

      - - + + diff --git a/reference/hotdeck.html b/reference/hotdeck.html index 8a75e3b..886780c 100644 --- a/reference/hotdeck.html +++ b/reference/hotdeck.html @@ -4,7 +4,7 @@ - +
- +

Hot-Deck Imputation

- Source: R/hotdeck.R + Source: R/hotdeck.R
@@ -93,55 +93,55 @@

Hot-Deck Imputation

Arguments

-
data
+ + +
data

data.frame or matrix

-
variable
+
variable

variables where missing values should be imputed (not overlapping with ord_var)

-
ord_var
+
ord_var

variables for sorting the data set before imputation (not overlapping with variable)

-
domain_var
+
domain_var

variables for building domains and impute within these domains

-
makeNA
+
makeNA

list of length equal to the number of variables, with values, that should be converted to NA for each variable

-
NAcond
+
NAcond

list of length equal to the number of variables, with a condition for imputing a NA

-
impNA
+
impNA

TRUE/FALSE whether NA should be imputed

-
donorcond
+
donorcond

list of length equal to the number of variables, with a donorcond condition as character string. e.g. ">5" or c(">5","<10). If the list element for a variable is NULL no condition will be applied for this variable.

-
imp_var
+
imp_var

TRUE/FALSE if a TRUE/FALSE variables for each imputed variable should be created show the imputation status

-
imp_suffix
+
imp_suffix

suffix for the TRUE/FALSE variables showing the imputation status

Value

- - -

the imputed data set.

+

the imputed data set.

Note

@@ -156,7 +156,7 @@

References

See also

-

Other imputation methods: +

Other imputation methods: impPCA(), irmi(), kNN(), @@ -219,15 +219,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/impPCA.html b/reference/impPCA.html index 12090da..a466cb4 100644 --- a/reference/impPCA.html +++ b/reference/impPCA.html @@ -3,7 +3,7 @@ - +
- +

Iterative EM PCA imputation

- Source: R/impPCA.R + Source: R/impPCA.R
@@ -89,44 +89,44 @@

Iterative EM PCA imputation

Arguments

-
x
+ + +
x

data.frame or matrix

-
method
+
method

"classical" or "mcd" (robust estimation)

-
m
+
m

number of multiple imputations (only if parameter boot equals TRUE)

-
eps
+
eps

threshold for convergence

-
k
+
k

number of principal components for reconstruction of x

-
maxit
+
maxit

maximum number of iterations

-
boot
+
boot

residual bootstrap (if TRUE)

-
verbose
+
verbose

TRUE/FALSE if additional information about the imputation process should be printed

Value

- - -

the imputed data set. If boot = FALSE this is a data.frame. +

the imputed data set. If boot = FALSE this is a data.frame. If boot = TRUE this is a list where each list element contains a data.frame.

@@ -137,7 +137,7 @@

References

See also

-

Other imputation methods: +

Other imputation methods: hotdeck(), irmi(), kNN(), @@ -612,15 +612,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/index.html b/reference/index.html index 5394c04..c689cc3 100644 --- a/reference/index.html +++ b/reference/index.html @@ -1,9 +1,9 @@ -Function reference • VIMPackage index • VIM - +
- +
@@ -325,15 +325,15 @@

Other

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/initialise.html b/reference/initialise.html index 162dc96..2847b39 100644 --- a/reference/initialise.html +++ b/reference/initialise.html @@ -3,7 +3,7 @@ - +
- +

Initialization of missing values

- Source: R/irmi.R + Source: R/irmi.R
@@ -80,20 +80,22 @@

Initialization of missing values

Arguments

-
x
+ + +
x

a vector.

-
mixed
+
mixed

a character vector containing the names of variables of type mixed (semi-continous).

-
method
+
method

Method used for Initialization (median or kNN)

-
mixed.constant
+
mixed.constant

vector with length equal to the number of semi-continuous variables specifying the point of the semi-continuous distribution with non-zero probability

@@ -101,9 +103,7 @@

Arguments

Value

- - -

the initialized vector.

+

the initialized vector.

Details

@@ -135,15 +135,15 @@

Author

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/irmi.html b/reference/irmi.html index e9d0ac2..2ab2136 100644 --- a/reference/irmi.html +++ b/reference/irmi.html @@ -4,7 +4,7 @@ - +
- +

Iterative robust model-based imputation (IRMI)

- Source: R/irmi.R + Source: R/irmi.R
@@ -105,119 +105,119 @@

Iterative robust model-based imputation (IRMI)

Arguments

-
x
+ + +
x

data.frame or matrix

-
eps
+
eps

threshold for convergency

-
maxit
+
maxit

maximum number of iterations

-
mixed
+
mixed

column index of the semi-continuous variables

-
mixed.constant
+
mixed.constant

vector with length equal to the number of semi-continuous variables specifying the point of the semi-continuous distribution with non-zero probability

-
count
+
count

column index of count variables

-
step
+
step

a stepwise model selection is applied when the parameter is set to TRUE

-
robust
+
robust

if TRUE, robust regression methods will be applied

-
takeAll
+
takeAll

takes information of (initialised) missings in the response as well for regression imputation.

-
noise
+
noise

irmi has the option to add a random error term to the imputed values, this creates the possibility for multiple imputation. The error term has mean 0 and variance corresponding to the variance of the regression residuals.

-
noise.factor
+
noise.factor

amount of noise.

-
force
+
force

if TRUE, the algorithm tries to find a solution in any case, possible by using different robust methods automatically.

-
robMethod
+
robMethod

regression method when the response is continuous. Default is MM-regression with lmrob.

-
force.mixed
+
force.mixed

if TRUE, the algorithm tries to find a solution in any case, possible by using different robust methods automatically.

-
mi
+
mi

number of multiple imputations.

-
addMixedFactors
+
addMixedFactors

if TRUE add additional factor variable for each mixed variable as X variable in the regression

-
trace
+
trace

Additional information about the iterations when trace equals TRUE.

-
init.method
+
init.method

Method for initialization of missing values (kNN or median)

-
modelFormulas
+
modelFormulas

a named list with the name of variables for the rhs of the formulas, which must contain a rhs formula for each variable with -missing values, it should look like `list(y1=c("x1","x2"),y2=c("x1","x3"))`` +missing values, it should look like `list(y1=c("x1","x2"),y2=c("x1","x3"))“ if factor variables for the mixed variables should be created for the regression models

-
multinom.method
+
multinom.method

Method for estimating the multinomial models (current default and only available method is multinom)

-
imp_var
+
imp_var

TRUE/FALSE if a TRUE/FALSE variables for each imputed variable should be created show the imputation status

-
imp_suffix
+
imp_suffix

suffix for the TRUE/FALSE variables showing the imputation status

Value

- - -

the imputed data set.

+

the imputed data set.

Details

@@ -237,7 +237,7 @@

References

See also

-

Other imputation methods: +

Other imputation methods: hotdeck(), impPCA(), kNN(), @@ -258,55 +258,9 @@

Examples


 data(sleep)
 irmi(sleep)
-#>  BodyWgt BrainWgt    Dream    Sleep     Span     Gest     Pred      Exp 
-#>    0.005    0.140    0.000    2.600    2.000   12.000    1.000    1.000 
-#>   Danger  BodyWgt BrainWgt    Dream    Sleep     Span     Gest     Pred 
-#>    1.000 6654.000 5712.000    6.600   19.900  100.000  645.000    5.000 
-#>      Exp   Danger 
-#>    5.000    5.000 
-#>  BodyWgt BrainWgt     NonD    Sleep     Span     Gest     Pred      Exp 
-#>    0.005    0.140    2.100    2.600    2.000   12.000    1.000    1.000 
-#>   Danger  BodyWgt BrainWgt     NonD    Sleep     Span     Gest     Pred 
-#>    1.000 6654.000 5712.000   17.900   19.900  100.000  645.000    5.000 
-#>      Exp   Danger 
-#>    5.000    5.000 
-#>  BodyWgt BrainWgt     NonD    Dream     Span     Gest     Pred      Exp 
-#>    0.005    0.140    2.100    0.000    2.000   12.000    1.000    1.000 
-#>   Danger  BodyWgt BrainWgt     NonD    Dream     Span     Gest     Pred 
-#>    1.000 6654.000 5712.000   17.900    6.600  100.000  645.000    5.000 
-#>      Exp   Danger 
-#>    5.000    5.000 
-#>  BodyWgt BrainWgt     NonD    Dream    Sleep     Gest     Pred      Exp 
-#>    0.005    0.140    2.100    0.000    2.600   12.000    1.000    1.000 
-#>   Danger  BodyWgt BrainWgt     NonD    Dream    Sleep     Gest     Pred 
-#>    1.000 6654.000 5712.000   17.900    6.600   19.900  645.000    5.000 
-#>      Exp   Danger 
-#>    5.000    5.000 
-#>  BodyWgt BrainWgt     NonD    Dream    Sleep     Span     Pred      Exp 
-#>    0.005    0.140    2.100    0.000    2.600    2.000    1.000    1.000 
-#>   Danger  BodyWgt BrainWgt     NonD    Dream    Sleep     Span     Pred 
-#>    1.000 6654.000 5712.000   17.900    6.600   19.900  100.000    5.000 
-#>      Exp   Danger 
-#>    5.000    5.000 
 
 data(testdata)
 imp_testdata1 <- irmi(testdata$wna, mixed = testdata$mixed)
-#>        x2        x2 
-#>  4.599866 15.039669 
-#>        x1        x1 
-#>  4.176996 15.235603 
-#>        x1        x2        x1        x2 
-#>  4.176996  4.599866 15.235603 15.039669 
-#>        x1        x2        x1        x2 
-#>  4.176996  4.599866 15.235603 15.039669 
-#>        x1        x2        x1        x2 
-#>  4.176996  4.599866 15.235603 15.039669 
-#>        x1        x2        x1        x2 
-#>  4.176996  4.599866 15.235603 15.039669 
-#>        x1        x2        x1        x2 
-#>  4.176996  4.599866 15.235603 15.039669 
-#>        x1        x2        x1        x2 
-#>  4.176996  4.599866 15.235603 15.039669 
 
 # mixed.constant != 0 (-10)
 testdata$wna$m1[testdata$wna$m1 == 0] <- -10
@@ -316,22 +270,6 @@ 
Examples

   mixed = testdata$mixed,
   mixed.constant = c(-10,log(0.001))
 )
-#>        x2        x2 
-#>  4.599866 15.039669 
-#>        x1        x1 
-#>  4.176996 15.235603 
-#>        x1        x2        x1        x2 
-#>  4.176996  4.599866 15.235603 15.039669 
-#>        x1        x2        x1        x2 
-#>  4.176996  4.599866 15.235603 15.039669 
-#>        x1        x2        x1        x2 
-#>  4.176996  4.599866 15.235603 15.039669 
-#>        x1        x2        x1        x2 
-#>  4.176996  4.599866 15.235603 15.039669 
-#>        x1        x2        x1        x2 
-#>  4.176996  4.599866 15.235603 15.039669 
-#>        x1        x2        x1        x2 
-#>  4.176996  4.599866 15.235603 15.039669 
 imp_testdata2$m2 <- exp(imp_testdata2$m2) - 0.001
 
 #example with fixed formulas for the variables with missing
@@ -344,36 +282,6 @@ 
Examples

 )
 irmi(sleep, modelFormulas = form, trace = TRUE)
 #> Method for multinomial models:multinom
-#>  BodyWgt BrainWgt    Dream    Sleep     Span     Gest     Pred      Exp 
-#>    0.005    0.140    0.000    2.600    2.000   12.000    1.000    1.000 
-#>   Danger  BodyWgt BrainWgt    Dream    Sleep     Span     Gest     Pred 
-#>    1.000 6654.000 5712.000    6.600   19.900  100.000  645.000    5.000 
-#>      Exp   Danger 
-#>    5.000    5.000 
-#>  BodyWgt BrainWgt     NonD    Sleep     Span     Gest     Pred      Exp 
-#>    0.005    0.140    2.100    2.600    2.000   12.000    1.000    1.000 
-#>   Danger  BodyWgt BrainWgt     NonD    Sleep     Span     Gest     Pred 
-#>    1.000 6654.000 5712.000   17.900   19.900  100.000  645.000    5.000 
-#>      Exp   Danger 
-#>    5.000    5.000 
-#>  BodyWgt BrainWgt     NonD    Dream     Span     Gest     Pred      Exp 
-#>    0.005    0.140    2.100    0.000    2.000   12.000    1.000    1.000 
-#>   Danger  BodyWgt BrainWgt     NonD    Dream     Span     Gest     Pred 
-#>    1.000 6654.000 5712.000   17.900    6.600  100.000  645.000    5.000 
-#>      Exp   Danger 
-#>    5.000    5.000 
-#>  BodyWgt BrainWgt     NonD    Dream    Sleep     Gest     Pred      Exp 
-#>    0.005    0.140    2.100    0.000    2.600   12.000    1.000    1.000 
-#>   Danger  BodyWgt BrainWgt     NonD    Dream    Sleep     Gest     Pred 
-#>    1.000 6654.000 5712.000   17.900    6.600   19.900  645.000    5.000 
-#>      Exp   Danger 
-#>    5.000    5.000 
-#>  BodyWgt BrainWgt     NonD    Dream    Sleep     Span     Pred      Exp 
-#>    0.005    0.140    2.100    0.000    2.600    2.000    1.000    1.000 
-#>   Danger  BodyWgt BrainWgt     NonD    Dream    Sleep     Span     Pred 
-#>    1.000 6654.000 5712.000   17.900    6.600   19.900  100.000    5.000 
-#>      Exp   Danger 
-#>    5.000    5.000 
 #>    BodyWgt BrainWgt NonD Dream Sleep Span Gest Pred Exp Danger
 #> 1 6654.000   5712.0  3.2   0.8   3.3 38.6  645    3   5      3
 #> 2    1.000      6.6  6.3   2.0   8.3  4.5   42    3   1      3
@@ -477,34 +385,10 @@ 
Examples

 #>               does not correspond to the values given in levOrders
 #> Warning: The number of unique values in the ordinal variables in data.y
 #>               does not correspond to the values given in levOrders
-#>         x2         m1         m2         x2         m1         m2 
-#>   4.599866 -10.000000  -6.907755  15.039669  13.741169   2.625980 
 #> Warning: The number of unique values in the ordinal variables in data.x
 #>               does not correspond to the values given in levOrders
 #> Warning: The number of unique values in the ordinal variables in data.y
 #>               does not correspond to the values given in levOrders
-#>         x1         m1         m2         x1         m1         m2 
-#>   4.176996 -10.000000  -6.907755  15.235603  13.741169   2.625980 
-#>         x1         x2         m1         m2         x1         x2         m1 
-#>   4.176996   4.599866 -10.000000  -6.907755  15.235603  15.039669  13.741169 
-#>         m2 
-#>   2.625980 
-#>         x1         x2         m1         m2         x1         x2         m1 
-#>   4.176996   4.599866 -10.000000  -6.907755  15.235603  15.039669  13.741169 
-#>         m2 
-#>   2.625980 
-#>         x1         x2         m1         m2         x1         x2         m1 
-#>   4.176996   4.599866 -10.000000  -6.907755  15.235603  15.039669  13.741169 
-#>         m2 
-#>   2.625980 
-#>         x1         x2         m1         m2         x1         x2         m1 
-#>   4.176996   4.599866 -10.000000  -6.907755  15.235603  15.039669  13.741169 
-#>         m2 
-#>   2.625980 
-#>        x1        x2        m2        x1        x2        m2 
-#>  4.176996  4.599866 -6.907755 15.235603 15.039669  2.625980 
-#>         x1         x2         m1         x1         x2         m1 
-#>   4.176996   4.599866 -10.000000  15.235603  15.039669  13.741169
@@ -520,15 +404,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/kNN.html b/reference/kNN.html index 68865e9..5311695 100644 --- a/reference/kNN.html +++ b/reference/kNN.html @@ -4,7 +4,7 @@ - +
- +

k-Nearest Neighbour Imputation

- Source: R/kNN.R + Source: R/kNN.R
@@ -106,117 +106,117 @@

k-Nearest Neighbour Imputation

Arguments

-
data
+ + +
data

data.frame or matrix

-
variable
+
variable

variables where missing values should be imputed

-
k
+
k

number of Nearest Neighbours used

-
dist_var
+
dist_var

names or variables to be used for distance calculation

-
weights
+
weights

weights for the variables for distance calculation. If weights = "auto" weights will be selected based on variable importance from random forest regression, using function ranger::ranger(). Weights are calculated for each variable seperately.

-
numFun
+
numFun

function for aggregating the k Nearest Neighbours in the case of a numerical variable

-
catFun
+
catFun

function for aggregating the k Nearest Neighbours in the case of a categorical variable

-
makeNA
+
makeNA

list of length equal to the number of variables, with values, that should be converted to NA for each variable

-
NAcond
+
NAcond

list of length equal to the number of variables, with a condition for imputing a NA

-
impNA
+
impNA

TRUE/FALSE whether NA should be imputed

-
donorcond
+
donorcond

list of length equal to the number of variables, with a donorcond condition as character string. e.g. a list element can be ">5" or c(">5","<10). If the list element for a variable is NULL no condition will be applied for this variable.

-
mixed
+
mixed

names of mixed variables

-
mixed.constant
+
mixed.constant

vector with length equal to the number of semi-continuous variables specifying the point of the semi-continuous distribution with non-zero probability

-
trace
+
trace

TRUE/FALSE if additional information about the imputation process should be printed

-
imp_var
+
imp_var

TRUE/FALSE if a TRUE/FALSE variables for each imputed variable should be created show the imputation status

-
imp_suffix
+
imp_suffix

suffix for the TRUE/FALSE variables showing the imputation status

-
addRF
+
addRF

TRUE/FALSE each variable will be modelled using random forest regression (ranger::ranger()) and used as additional distance variable.

-
onlyRF
+
onlyRF

TRUE/FALSE if TRUE only additional distance variables created from random forest regression will be used as distance variables.

-
addRandom
+
addRandom

TRUE/FALSE if an additional random variable should be added for distance calculation

-
useImputedDist
+
useImputedDist

TRUE/FALSE if an imputed value should be used for distance calculation for imputing another variable. Be aware that this results in a dependency on the ordering of the variables.

-
weightDist
+
weightDist

TRUE/FALSE if the distances of the k nearest neighbours should be used as weights in the aggregation step

-
methodStand
+
methodStand

either "range" or "iqr" to be used in the standardization of numeric vaiables in the gower distance

-
ordFun
+
ordFun

function for aggregating the k Nearest Neighbours in the case of a ordered factor variable

Value

- - -

the imputed data set.

+

the imputed data set.

References

@@ -226,7 +226,7 @@

References

See also

-

Other imputation methods: +

Other imputation methods: hotdeck(), impPCA(), irmi(), @@ -247,36 +247,6 @@

Examples


 data(sleep)
 kNN(sleep)
-#>  BodyWgt BrainWgt    Dream    Sleep     Span     Gest     Pred      Exp 
-#>    0.005    0.140    0.000    2.600    2.000   12.000    1.000    1.000 
-#>   Danger  BodyWgt BrainWgt    Dream    Sleep     Span     Gest     Pred 
-#>    1.000 6654.000 5712.000    6.600   19.900  100.000  645.000    5.000 
-#>      Exp   Danger 
-#>    5.000    5.000 
-#>  BodyWgt BrainWgt     NonD    Sleep     Span     Gest     Pred      Exp 
-#>    0.005    0.140    2.100    2.600    2.000   12.000    1.000    1.000 
-#>   Danger  BodyWgt BrainWgt     NonD    Sleep     Span     Gest     Pred 
-#>    1.000 6654.000 5712.000   17.900   19.900  100.000  645.000    5.000 
-#>      Exp   Danger 
-#>    5.000    5.000 
-#>  BodyWgt BrainWgt     NonD    Dream     Span     Gest     Pred      Exp 
-#>    0.005    0.140    2.100    0.000    2.000   12.000    1.000    1.000 
-#>   Danger  BodyWgt BrainWgt     NonD    Dream     Span     Gest     Pred 
-#>    1.000 6654.000 5712.000   17.900    6.600  100.000  645.000    5.000 
-#>      Exp   Danger 
-#>    5.000    5.000 
-#>  BodyWgt BrainWgt     NonD    Dream    Sleep     Gest     Pred      Exp 
-#>    0.005    0.140    2.100    0.000    2.600   12.000    1.000    1.000 
-#>   Danger  BodyWgt BrainWgt     NonD    Dream    Sleep     Gest     Pred 
-#>    1.000 6654.000 5712.000   17.900    6.600   19.900  645.000    5.000 
-#>      Exp   Danger 
-#>    5.000    5.000 
-#>  BodyWgt BrainWgt     NonD    Dream    Sleep     Span     Pred      Exp 
-#>    0.005    0.140    2.100    0.000    2.600    2.000    1.000    1.000 
-#>   Danger  BodyWgt BrainWgt     NonD    Dream    Sleep     Span     Pred 
-#>    1.000 6654.000 5712.000   17.900    6.600   19.900  100.000    5.000 
-#>      Exp   Danger 
-#>    5.000    5.000 
 #>     BodyWgt BrainWgt NonD Dream Sleep  Span  Gest Pred Exp Danger BodyWgt_imp
 #> 1  6654.000  5712.00  3.2   0.8   3.3  38.6 645.0    3   5      3       FALSE
 #> 2     1.000     6.60  6.3   2.0   8.3   4.5  42.0    3   1      3       FALSE
@@ -468,36 +438,6 @@ 
Examples

 #> 62      FALSE
 library(laeken)
 kNN(sleep, numFun = weightedMean, weightDist=TRUE)
-#>  BodyWgt BrainWgt    Dream    Sleep     Span     Gest     Pred      Exp 
-#>    0.005    0.140    0.000    2.600    2.000   12.000    1.000    1.000 
-#>   Danger  BodyWgt BrainWgt    Dream    Sleep     Span     Gest     Pred 
-#>    1.000 6654.000 5712.000    6.600   19.900  100.000  645.000    5.000 
-#>      Exp   Danger 
-#>    5.000    5.000 
-#>  BodyWgt BrainWgt     NonD    Sleep     Span     Gest     Pred      Exp 
-#>    0.005    0.140    2.100    2.600    2.000   12.000    1.000    1.000 
-#>   Danger  BodyWgt BrainWgt     NonD    Sleep     Span     Gest     Pred 
-#>    1.000 6654.000 5712.000   17.900   19.900  100.000  645.000    5.000 
-#>      Exp   Danger 
-#>    5.000    5.000 
-#>  BodyWgt BrainWgt     NonD    Dream     Span     Gest     Pred      Exp 
-#>    0.005    0.140    2.100    0.000    2.000   12.000    1.000    1.000 
-#>   Danger  BodyWgt BrainWgt     NonD    Dream     Span     Gest     Pred 
-#>    1.000 6654.000 5712.000   17.900    6.600  100.000  645.000    5.000 
-#>      Exp   Danger 
-#>    5.000    5.000 
-#>  BodyWgt BrainWgt     NonD    Dream    Sleep     Gest     Pred      Exp 
-#>    0.005    0.140    2.100    0.000    2.600   12.000    1.000    1.000 
-#>   Danger  BodyWgt BrainWgt     NonD    Dream    Sleep     Gest     Pred 
-#>    1.000 6654.000 5712.000   17.900    6.600   19.900  645.000    5.000 
-#>      Exp   Danger 
-#>    5.000    5.000 
-#>  BodyWgt BrainWgt     NonD    Dream    Sleep     Span     Pred      Exp 
-#>    0.005    0.140    2.100    0.000    2.600    2.000    1.000    1.000 
-#>   Danger  BodyWgt BrainWgt     NonD    Dream    Sleep     Span     Pred 
-#>    1.000 6654.000 5712.000   17.900    6.600   19.900  100.000    5.000 
-#>      Exp   Danger 
-#>    5.000    5.000 
 #>     BodyWgt BrainWgt      NonD     Dream     Sleep       Span      Gest Pred
 #> 1  6654.000  5712.00  3.621115 1.0244651  3.300000  38.600000 645.00000    3
 #> 2     1.000     6.60  6.300000 2.0000000  8.300000   4.500000  42.00000    3
@@ -702,15 +642,15 @@ 
Examples
-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/kola.background.html b/reference/kola.background.html index e6f1123..ee23991 100644 --- a/reference/kola.background.html +++ b/reference/kola.background.html @@ -3,7 +3,7 @@ - +
- +

Background map for the Kola project data

- Source: R/VIM-package.R + Source: R/VIM-package.R
@@ -107,15 +107,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/libs/reactwidget-2.0.0/react-tools.umd.cjs b/reference/libs/reactwidget-2.0.0/react-tools.umd.cjs new file mode 100644 index 0000000..159c7ab --- /dev/null +++ b/reference/libs/reactwidget-2.0.0/react-tools.umd.cjs @@ -0,0 +1 @@ +(function(s,u){typeof exports=="object"&&typeof module<"u"?u(exports):typeof define=="function"&&define.amd?define(["exports"],u):(s=typeof globalThis<"u"?globalThis:s||self,u(s.reactR={}))})(this,function(s){"use strict";function u(n,t){if(typeof t=="string")return t;if(t.name[0]===t.name[0].toUpperCase()&&!n.hasOwnProperty(t.name))throw new Error("Unknown component: "+t.name);for(let i in t.attribs)g(t.attribs[i])&&(t.attribs[i]=u(n,t.attribs[i]));for(var a=n.hasOwnProperty(t.name)?n[t.name]:t.name,r=[a,t.attribs],e=0;e - +
- +

Map with information about missing/imputed values

- Source: R/mapMiss.R + Source: R/mapMiss.R
@@ -93,20 +93,22 @@

Map with information about missing/imputed values

Arguments

-
x
+ + +
x

a vector, matrix or data.frame.

-
coords
+
coords

a data.frame or matrix with two columns giving the spatial coordinates of the observations.

-
map
+
map

a background map to be passed to bgmap().

-
delimiter
+
delimiter

a character-vector to distinguish between variables and imputation-indices for imputed variables (therefore, x needs to have colnames()). If given, it is used to determine the corresponding @@ -116,45 +118,45 @@

Arguments

to the given colors for imputed variables (see col).

-
selection
+
selection

the selection method for displaying missing/imputed values in the map. Possible values are "any" (display missing/imputed values in any variable) and "all" (display missing/imputed values in all variables).

-
col
+
col

a vector of length three giving the colors to be used for observed, missing and imputed values. If a single color is supplied, it is used for all values.

-
alpha
+
alpha

a numeric value between 0 and 1 giving the level of transparency of the colors, or NULL. This can be used to prevent overplotting.

-
pch
+
pch

a vector of length two giving the plot characters to be used for observed and missing/imputed values. If a single plot character is supplied, it will be used for both.

-
col.map
+
col.map

the color to be used for the background map.

-
legend
+
legend

a logical indicating whether a legend should be plotted.

-
interactive
+
interactive

a logical indicating whether information about selected observations can be displayed interactively (see ‘Details’).

-
...
+
...

further graphical parameters to be passed to bgmap() and graphics::points().

@@ -198,10 +200,6 @@

Examples

## for imputed values x_imp <- kNN(chorizonDL[, c("As", "Bi")]) -#> Bi Bi -#> 0.006 3.890 -#> As As -#> 0.1 30.7 mapMiss(x_imp, coo, kola.background, delimiter = "_imp") #> @@ -223,15 +221,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/marginmatrix.html b/reference/marginmatrix.html index 178fadc..119afea 100644 --- a/reference/marginmatrix.html +++ b/reference/marginmatrix.html @@ -4,7 +4,7 @@ - +
- +

Marginplot Matrix

- Source: R/marginmatrix.R + Source: R/marginmatrix.R
@@ -88,11 +88,13 @@

Marginplot Matrix

Arguments

-
x
+ + +
x

a matrix or data.frame.

-
delimiter
+
delimiter

a character-vector to distinguish between variables and imputation-indices for imputed variables (therefore, x needs to have colnames()). If given, it is used to determine the corresponding @@ -102,7 +104,7 @@

Arguments

to the given colors for imputed variables (see col).

-
col
+
col

a vector of length five giving the colors to be used in the marginplots in the off-diagonal panels. The first color is used for the scatterplot and the boxplots for the available data, the second/fourth color @@ -115,13 +117,13 @@

Arguments

colors are supplied, the second one is recycled.

-
alpha
+
alpha

a numeric value between 0 and 1 giving the level of transparency of the colors, or NULL. This can be used to prevent overplotting.

-
...
+
...

further arguments and graphical parameters to be passed to pairsVIM() and marginplot(). par("oma") will be set appropriately unless supplied (see graphics::par()).

@@ -144,7 +146,7 @@

References

See also

marginplot(), pairsVIM(), scattmatrixMiss()

-

Other plotting functions: +

Other plotting functions: aggr(), barMiss(), histMiss(), @@ -185,12 +187,6 @@

Examples

## for imputed values x_imp <- kNN(sleep[, 1:5]) -#> BodyWgt BrainWgt Dream Sleep BodyWgt BrainWgt Dream Sleep -#> 0.005 0.140 0.000 2.600 6654.000 5712.000 6.600 19.900 -#> BodyWgt BrainWgt NonD Sleep BodyWgt BrainWgt NonD Sleep -#> 0.005 0.140 2.100 2.600 6654.000 5712.000 17.900 19.900 -#> BodyWgt BrainWgt NonD Dream BodyWgt BrainWgt NonD Dream -#> 0.005 0.140 2.100 0.000 6654.000 5712.000 17.900 6.600 x_imp[,c(1,2,4)] <- log10(x_imp[,c(1,2,4)]) marginmatrix(x_imp, delimiter = "_imp") #> Warning: variable 'Dream' contains infinite values @@ -218,15 +214,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/marginplot.html b/reference/marginplot.html index 6fcf131..6925cec 100644 --- a/reference/marginplot.html +++ b/reference/marginplot.html @@ -5,7 +5,7 @@ - +
- +

Scatterplot with additional information in the margins

- Source: R/marginplot.R + Source: R/marginplot.R
@@ -104,11 +104,13 @@

Scatterplot with additional information in the margins

Arguments

-
x
+ + +
x

a matrix or data.frame with two columns.

-
delimiter
+
delimiter

a character-vector to distinguish between variables and imputation-indices for imputed variables (therefore, x needs to have colnames()). If given, it is used to determine the corresponding @@ -118,7 +120,7 @@

Arguments

to the given colors for imputed variables (see col).

-
col
+
col

a vector of length five giving the colors to be used in the plot. The first color is used for the scatterplot and the boxplots for the available data. In case of missing values, the second color is taken for the @@ -135,71 +137,71 @@

Arguments

colors are supplied, the second one is recycled.

-
alpha
+
alpha

a numeric value between 0 and 1 giving the level of transparency of the colors, or NULL. This can be used to prevent overplotting.

-
pch
+
pch

a vector of length two giving the plot symbols to be used for the scatterplot and the univariate scatterplots. If a single plot character is supplied, it is used for the scatterplot and the default value will be used for the univariate scatterplots (see ‘Details’).

-
cex
+
cex

the character expansion factor to be used for the bivariate and univariate scatterplots.

-
numbers
+
numbers

a logical indicating whether the frequencies of missing/imputed values should be displayed in the lower left of the plot (see ‘Details’).

-
cex.numbers
+
cex.numbers

the character expansion factor to be used for the frequencies of the missing/imputed values.

-
zeros
+
zeros

a logical vector of length two indicating whether the variables are semi-continuous, i.e., contain a considerable amount of zeros. If TRUE, only the non-zero observations are used for drawing the respective boxplot. If a single logical is supplied, it is recycled.

-
xlim, ylim
+
xlim, ylim

axis limits.

-
main, sub
+
main, sub

main and sub title.

-
xlab, ylab
+
xlab, ylab

axis labels.

-
ann
+
ann

a logical indicating whether plot annotation (main, sub, xlab, ylab) should be displayed.

-
axes
+
axes

a logical indicating whether both axes should be drawn on the plot. Use graphical parameter "xaxt" or "yaxt" to suppress only one of the axes.

-
frame.plot
+
frame.plot

a logical indicating whether a box should be drawn around the plot.

-
...
+
...

further graphical parameters to be passed down (see graphics::par()).

@@ -233,7 +235,7 @@

References

See also

scattMiss()

-

Other plotting functions: +

Other plotting functions: aggr(), barMiss(), histMiss(), @@ -267,14 +269,8 @@

Examples

## for imputed values marginplot(kNN(tao[,c("Air.Temp", "Humidity")]), delimiter = "_imp") -#> Humidity Humidity -#> 71.6 94.8 -#> Air.Temp Air.Temp -#> 21.42 28.50 marginplot(kNN(log10(chorizonDL[,c("CaO", "Bi")])), delimiter = "_imp") -#> CaO CaO -#> -1.3010300 0.9758911 @@ -292,15 +288,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/matchImpute.html b/reference/matchImpute.html index 7123cbf..67cda7b 100644 --- a/reference/matchImpute.html +++ b/reference/matchImpute.html @@ -5,7 +5,7 @@ - +
- +

Fast matching/imputation based on categorical variable

- Source: R/matchImpute.R + Source: R/matchImpute.R
@@ -90,33 +90,33 @@

Fast matching/imputation based on categorical variable

Arguments

-
data
+ + +
data

data.frame, data.table or matrix

-
variable
+
variable

variables to be imputed

-
match_var
+
match_var

variables used for matching

-
imp_var
+
imp_var

TRUE/FALSE if a TRUE/FALSE variables for each imputed variable should be created show the imputation status

-
imp_suffix
+
imp_suffix

suffix for the TRUE/FALSE variables showing the imputation status

Value

- - -

the imputed data set.

+

the imputed data set.

Details

@@ -125,7 +125,7 @@

Details

See also

hotdeck()

-

Other imputation methods: +

Other imputation methods: hotdeck(), impPCA(), irmi(), @@ -167,15 +167,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/matrixplot.html b/reference/matrixplot.html index 70d6067..8a1005c 100644 --- a/reference/matrixplot.html +++ b/reference/matrixplot.html @@ -5,7 +5,7 @@ - +
- +

Matrix plot

- Source: R/matrixplot.R + Source: R/matrixplot.R
@@ -101,11 +101,13 @@

Matrix plot

Arguments

-
x
+ + +
x

a matrix or data.frame.

-
delimiter
+
delimiter

a character-vector to distinguish between variables and imputation-indices for imputed variables (therefore, x needs to have colnames()). If given, it is used to determine the corresponding @@ -115,12 +117,12 @@

Arguments

to the given colors for imputed variables (see col).

-
sortby
+
sortby

a numeric or character value specifying the variable to sort the data matrix by, or NULL to plot without sorting.

-
col
+
col

the colors to be used in the plot. RGB colors may be specified as character strings or as objects of class "colorspace::RGB()". HCL colors need to be specified as objects of class @@ -136,44 +138,44 @@

Arguments

for missing/imputed data.

-
fixup
+
fixup

a logical indicating whether the colors should be corrected to valid RGB values (see colorspace::hex()).

-
xlim, ylim
+
xlim, ylim

axis limits.

-
main, sub
+
main, sub

main and sub title.

-
xlab, ylab
+
xlab, ylab

axis labels.

-
axes
+
axes

a logical indicating whether axes should be drawn on the plot.

-
labels
+
labels

either a logical indicating whether labels should be plotted below each column, or a character vector giving the labels.

-
xpd
+
xpd

a logical indicating whether the rectangles should be allowed to go outside the plot region. If NULL, it defaults to TRUE unless axis limits are specified.

-
interactive
+
interactive

a logical indicating whether a variable to be used for sorting can be selected interactively (see ‘Details’).

-
...
+
...

for matrixplot and iimagMiss, further graphical parameters to be passed to graphics::plot.window(), graphics::title() and graphics::axis(). For @@ -213,7 +215,7 @@

References

See also

-

Other plotting functions: +

Other plotting functions: aggr(), barMiss(), histMiss(), @@ -246,26 +248,6 @@

Examples

## for imputed values x_imp <- kNN(sleep[, -(8:10)]) -#> BodyWgt BrainWgt Dream Sleep Span Gest BodyWgt BrainWgt -#> 0.005 0.140 0.000 2.600 2.000 12.000 6654.000 5712.000 -#> Dream Sleep Span Gest -#> 6.600 19.900 100.000 645.000 -#> BodyWgt BrainWgt NonD Sleep Span Gest BodyWgt BrainWgt -#> 0.005 0.140 2.100 2.600 2.000 12.000 6654.000 5712.000 -#> NonD Sleep Span Gest -#> 17.900 19.900 100.000 645.000 -#> BodyWgt BrainWgt NonD Dream Span Gest BodyWgt BrainWgt -#> 0.005 0.140 2.100 0.000 2.000 12.000 6654.000 5712.000 -#> NonD Dream Span Gest -#> 17.900 6.600 100.000 645.000 -#> BodyWgt BrainWgt NonD Dream Sleep Gest BodyWgt BrainWgt -#> 0.005 0.140 2.100 0.000 2.600 12.000 6654.000 5712.000 -#> NonD Dream Sleep Gest -#> 17.900 6.600 19.900 645.000 -#> BodyWgt BrainWgt NonD Dream Sleep Span BodyWgt BrainWgt -#> 0.005 0.140 2.100 0.000 2.600 2.000 6654.000 5712.000 -#> NonD Dream Sleep Span -#> 17.900 6.600 19.900 100.000 x_imp[,c(1,2,4,6,7)] <- log10(x_imp[,c(1,2,4,6,7)]) matrixplot(x_imp, delimiter = "_imp", sortby = "BrainWgt") #> Warning: variable 'Dream' contains infinite values @@ -285,15 +267,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/maxCat.html b/reference/maxCat.html index 8de23e1..199d45e 100644 --- a/reference/maxCat.html +++ b/reference/maxCat.html @@ -4,7 +4,7 @@ - +
- +

Aggregation function for a factor variable

- Source: R/maxCat.R + Source: R/maxCat.R
@@ -82,11 +82,13 @@

Aggregation function for a factor variable

Arguments

-
x
+ + +
x

factor vector

-
weights
+
weights

numeric vector providing weights for the observations in x

@@ -103,15 +105,15 @@

Arguments

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/medianSamp.html b/reference/medianSamp.html index d1afd61..e432e25 100644 --- a/reference/medianSamp.html +++ b/reference/medianSamp.html @@ -4,7 +4,7 @@ - +
- +

Aggregation function for a ordinal variable

- Source: R/medianSamp.R + Source: R/medianSamp.R
@@ -82,17 +82,19 @@

Aggregation function for a ordinal variable

Arguments

-
x
+ + +
x

ordered factor vector

-
weights
+
weights

numeric vector providing weights for the observations in x

See also

-

Other imputation methods: +

Other imputation methods: hotdeck(), impPCA(), irmi(), @@ -116,15 +118,15 @@

See also

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/mosaicMiss.html b/reference/mosaicMiss.html index fc8c02d..189bd51 100644 --- a/reference/mosaicMiss.html +++ b/reference/mosaicMiss.html @@ -3,7 +3,7 @@ - +
- +

Mosaic plot with information about missing/imputed values

- Source: R/mosaicMiss.R + Source: R/mosaicMiss.R
@@ -90,11 +90,13 @@

Mosaic plot with information about missing/imputed values

Arguments

-
x
+ + +
x

a matrix or data.frame.

-
delimiter
+
delimiter

a character-vector to distinguish between variables and imputation-indices for imputed variables (therefore, x needs to have colnames()). If given, it is used to determine the corresponding @@ -104,12 +106,12 @@

Arguments

to the given colors for imputed variables (see col).

-
highlight
+
highlight

a vector giving the variables to be used for highlighting. If NULL (the default), all variables are used for highlighting.

-
selection
+
selection

the selection method for highlighting missing/imputed values in multiple highlight variables. Possible values are "any" (highlighting of missing/imputed values in any of the highlight @@ -117,38 +119,36 @@

Arguments

all of the highlight variables).

-
plotvars
+
plotvars

a vector giving the categorical variables to be plotted. If NULL (the default), all variables are plotted.

-
col
+
col

a vector of length three giving the colors to be used for observed, missing and imputed data. If only one color is supplied, the tiles corresponding to observed data are transparent and the supplied color is used for highlighting.

-
labels
+
labels

a list of arguments for the labeling function vcd::labeling_border().

-
miss.labels
+
miss.labels

either a logical indicating whether labels should be plotted for observed and missing/imputed (highlighted) data, or a character vector giving the labels.

-
...
+
...

additional arguments to be passed to vcd::mosaic().

Value

- - -

An object of class "structable" is returned invisibly.

+

An object of class "structable" is returned invisibly.

Details

@@ -168,7 +168,7 @@

Note

References

Meyer, D., Zeileis, A. and Hornik, K. (2006) The strucplot framework: Visualizing multi-way contingency tables with -vcd. Journal of Statistical Software, 17 (3), 1--48.

+vcd. Journal of Statistical Software, 17 (3), 1–48.

M. Templ, A. Alfons, P. Filzmoser (2012) Exploring incomplete data using visualization tools. Journal of Advances in Data Analysis and Classification, Online first. DOI: 10.1007/s11634-011-0102-y.

@@ -176,7 +176,7 @@

References

See also

spineMiss(), vcd::mosaic()

-

Other plotting functions: +

Other plotting functions: aggr(), barMiss(), histMiss(), @@ -208,36 +208,6 @@

Examples

## for imputed values mosaicMiss(kNN(sleep), highlight = 4, plotvars = 8:10, delimiter = "_imp", miss.labels = FALSE) -#> BodyWgt BrainWgt Dream Sleep Span Gest Pred Exp -#> 0.005 0.140 0.000 2.600 2.000 12.000 1.000 1.000 -#> Danger BodyWgt BrainWgt Dream Sleep Span Gest Pred -#> 1.000 6654.000 5712.000 6.600 19.900 100.000 645.000 5.000 -#> Exp Danger -#> 5.000 5.000 -#> BodyWgt BrainWgt NonD Sleep Span Gest Pred Exp -#> 0.005 0.140 2.100 2.600 2.000 12.000 1.000 1.000 -#> Danger BodyWgt BrainWgt NonD Sleep Span Gest Pred -#> 1.000 6654.000 5712.000 17.900 19.900 100.000 645.000 5.000 -#> Exp Danger -#> 5.000 5.000 -#> BodyWgt BrainWgt NonD Dream Span Gest Pred Exp -#> 0.005 0.140 2.100 0.000 2.000 12.000 1.000 1.000 -#> Danger BodyWgt BrainWgt NonD Dream Span Gest Pred -#> 1.000 6654.000 5712.000 17.900 6.600 100.000 645.000 5.000 -#> Exp Danger -#> 5.000 5.000 -#> BodyWgt BrainWgt NonD Dream Sleep Gest Pred Exp -#> 0.005 0.140 2.100 0.000 2.600 12.000 1.000 1.000 -#> Danger BodyWgt BrainWgt NonD Dream Sleep Gest Pred -#> 1.000 6654.000 5712.000 17.900 6.600 19.900 645.000 5.000 -#> Exp Danger -#> 5.000 5.000 -#> BodyWgt BrainWgt NonD Dream Sleep Span Pred Exp -#> 0.005 0.140 2.100 0.000 2.600 2.000 1.000 1.000 -#> Danger BodyWgt BrainWgt NonD Dream Sleep Span Pred -#> 1.000 6654.000 5712.000 17.900 6.600 19.900 100.000 5.000 -#> Exp Danger -#> 5.000 5.000
@@ -254,15 +224,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/pairsVIM.html b/reference/pairsVIM.html index 99d79c7..98d0327 100644 --- a/reference/pairsVIM.html +++ b/reference/pairsVIM.html @@ -3,7 +3,7 @@ - +
- +

Scatterplot Matrices

- Source: R/pairsVIM.R + Source: R/pairsVIM.R
@@ -96,17 +96,19 @@

Scatterplot Matrices

Arguments

-
x
+ + +
x

a matrix or data.frame.

-
...
+
...

further arguments and graphical parameters to be passed down. par("oma") will be set appropriately unless supplied (see graphics::par()).

-
delimiter
+
delimiter

a character-vector to distinguish between variables and imputation-indices for imputed variables (therefore, x needs to have colnames()). If given, it is used to determine the corresponding @@ -116,51 +118,51 @@

Arguments

to the given colors for imputed variables (see col).

-
main, sub
+
main, sub

main and sub title.

-
panel
+
panel

a function(x, y, ...{}), which is used to plot the contents of each off-diagonal panel of the display.

-
lower, upper
+
lower, upper

separate panel functions to be used below and above the diagonal, respectively.

-
diagonal
+
diagonal

optional function(x, ...{}) to be applied on the diagonal panels.

-
labels
+
labels

either a logical indicating whether labels should be plotted in the diagonal panels, or a character vector giving the labels.

-
pos.labels
+
pos.labels

the vertical position of the labels in the diagonal panels.

-
cex.labels
+
cex.labels

the character expansion factor to be used for the labels.

-
font.labels
+
font.labels

the font to be used for the labels.

-
layout
+
layout

a character string giving the layout of the scatterplot matrix. Possible values are "matrix" (a matrix-like layout with the first row on top) and "graph" (a graph-like layout with the first row at the bottom).

-
gap
+
gap

a numeric value giving the distance between the panels in margin lines.

@@ -189,7 +191,7 @@

References

See also

marginmatrix(), scattmatrixMiss()

-

Other plotting functions: +

Other plotting functions: aggr(), barMiss(), histMiss(), @@ -233,15 +235,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/parcoordMiss.html b/reference/parcoordMiss.html index 1352b0d..9cc5301 100644 --- a/reference/parcoordMiss.html +++ b/reference/parcoordMiss.html @@ -7,7 +7,7 @@ - +
- +

Parallel coordinate plot with information about missing/imputed values

- Source: R/parcoordMiss.R + Source: R/parcoordMiss.R
@@ -108,11 +108,13 @@

Parallel coordinate plot with information about missing/imputed values

Arguments

-
x
+ + +
x

a matrix or data.frame.

-
delimiter
+
delimiter

a character-vector to distinguish between variables and imputation-indices for imputed variables (therefore, x needs to have colnames()). If given, it is used to determine the corresponding @@ -122,12 +124,12 @@

Arguments

to the given colors for imputed variables (see col).

-
highlight
+
highlight

a vector giving the variables to be used for highlighting. If NULL (the default), all variables are used for highlighting.

-
selection
+
selection

the selection method for highlighting missing/imputed values in multiple highlight variables. Possible values are "any" (highlighting of missing/imputed values in any of the highlight @@ -135,18 +137,18 @@

Arguments

all of the highlight variables).

-
plotvars
+
plotvars

a vector giving the variables to be plotted. If NULL (the default), all variables are plotted.

-
plotNA
+
plotNA

a logical indicating whether missing values in the plot variables should be represented by a point above the corresponding coordinate axis to prevent disconnected lines.

-
col
+
col

if plotNA is TRUE, a vector of length six giving the colors to be used for observations with different combinations of observed and missing/imputed values in the plot variables and highlight @@ -155,13 +157,13 @@

Arguments

observations (if a single color is supplied, it is used for both).

-
alpha
+
alpha

a numeric value between 0 and 1 giving the level of transparency of the colors, or NULL. This can be used to prevent overplotting.

-
lty
+
lty

if plotNA is TRUE, a vector of length four giving the line types to be used for observations with different combinations of observed and missing/imputed values in the plot variables and highlight @@ -170,35 +172,35 @@

Arguments

observations (if a single line type is supplied, it is used for both).

-
xlim, ylim
+
xlim, ylim

axis limits.

-
main, sub
+
main, sub

main and sub title.

-
xlab, ylab
+
xlab, ylab

axis labels.

-
labels
+
labels

either a logical indicating whether labels should be plotted below each coordinate axis, or a character vector giving the labels.

-
xpd
+
xpd

a logical indicating whether the lines should be allowed to go outside the plot region. If NULL, it defaults to TRUE unless axis limits are specified.

-
interactive
+
interactive

a logical indicating whether interactive features should be enabled (see ‘Details’).

-
...
+
...

for parcoordMiss, further graphical parameters to be passed down (see graphics::par()). For TKRparcoordMiss, further arguments to be passed to parcoordMiss.

@@ -241,7 +243,7 @@

Note

References

Wegman, E. J. (1990) Hyperdimensional data analysis using parallel coordinates. Journal of the American Statistical Association -85 (411), 664--675.

+85 (411), 664–675.

M. Templ, A. Alfons, P. Filzmoser (2012) Exploring incomplete data using visualization tools. Journal of Advances in Data Analysis and Classification, Online first. DOI: 10.1007/s11634-011-0102-y.

@@ -249,7 +251,7 @@

References

See also

pbox()

-

Other plotting functions: +

Other plotting functions: aggr(), barMiss(), histMiss(), @@ -283,10 +285,6 @@

Examples

## for imputed values parcoordMiss(kNN(chorizonDL[,c(15,101:110)]), delimiter = "_imp" , plotvars=2:11, interactive = FALSE) -#> Al_XRF Ca_XRF Fe_XRF K_XRF Mg_XRF Mn_XRF Na_XRF P_XRF Si_XRF Ti_XRF Al_XRF -#> 2.920 0.030 0.590 0.360 0.120 0.015 0.080 0.004 17.050 0.053 12.080 -#> Ca_XRF Fe_XRF K_XRF Mg_XRF Mn_XRF Na_XRF P_XRF Si_XRF Ti_XRF -#> 6.760 12.350 5.240 7.320 0.356 4.870 0.589 40.270 1.900 legend("top", col = c("skyblue", "orange"), lwd = c(1,1), legend = c("observed in Bi", "imputed in Bi")) @@ -305,15 +303,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/pbox.html b/reference/pbox.html index 9c10a2c..66ed2f1 100644 --- a/reference/pbox.html +++ b/reference/pbox.html @@ -4,7 +4,7 @@ - +
- +

Parallel boxplots with information about missing/imputed values

- Source: R/pbox.R + Source: R/pbox.R
@@ -101,11 +101,13 @@

Parallel boxplots with information about missing/imputed values

Arguments

-
x
+ + +
x

a vector, matrix or data.frame.

-
delimiter
+
delimiter

a character-vector to distinguish between variables and imputation-indices for imputed variables (therefore, x needs to have colnames()). If given, it is used to determine the corresponding @@ -115,13 +117,13 @@

Arguments

to the given colors for imputed variables (see col).

-
pos
+
pos

a numeric value giving the index of the variable of interest. Additional variables in x are used for grouping according to missingness/number of imputed missings.

-
selection
+
selection

the selection method for grouping according to missingness/number of imputed missings in multiple additional variables. Possible values are "none" (grouping according to missingness/number @@ -132,7 +134,7 @@

Arguments

of the additional variables).

-
col
+
col

a vector of length five giving the colors to be used in the plot. The first color is used for the boxplots of the available data, the second/fourth are used for missing/imputed data, respectively, and the @@ -143,48 +145,48 @@

Arguments

one is recycled.

-
numbers
+
numbers

a logical indicating whether the frequencies of missing/imputed values should be displayed (see ‘Details’).

-
cex.numbers
+
cex.numbers

the character expansion factor to be used for the frequencies of the missing/imputed values.

-
xlim, ylim
+
xlim, ylim

axis limits.

-
main, sub
+
main, sub

main and sub title.

-
xlab, ylab
+
xlab, ylab

axis labels.

-
axes
+
axes

a logical indicating whether axes should be drawn on the plot.

-
frame.plot
+
frame.plot

a logical indicating whether a box should be drawn around the plot.

-
labels
+
labels

either a logical indicating whether labels should be plotted below each box, or a character vector giving the labels.

-
interactive
+
interactive

a logical indicating whether variables can be switched interactively (see ‘Details’).

-
...
+
...

for pbox, further arguments and graphical parameters to be passed to graphics::boxplot() and other functions. For TKRpbox, further arguments to be passed to pbox.

@@ -192,9 +194,7 @@

Arguments

Value

- - -

a list as returned by graphics::boxplot().

+

a list as returned by graphics::boxplot().

Details

@@ -229,7 +229,7 @@

References

See also

parcoordMiss()

-

Other plotting functions: +

Other plotting functions: aggr(), barMiss(), histMiss(), @@ -260,94 +260,6 @@

Examples

## for imputed values pbox(kNN(log(chorizonDL[, c(4,8,10,11,17,19,25,29,37,38,40)])), delimiter = "_imp") -#> As Au_INAA B Br_INAA Ca_INAA Co_INAA -#> -2.30258509 -6.21460810 1.09861229 0.09531018 9.21034037 1.09861229 -#> Cs_INAA Hg Hg_INAA K As Au_INAA -#> 0.00000000 -3.91202301 0.00000000 5.29831737 3.42426265 -0.01918282 -#> B Br_INAA Ca_INAA Co_INAA Cs_INAA Hg -#> 2.39789527 4.02535169 11.00209984 4.04305127 2.07944154 -1.83258146 -#> Hg_INAA K -#> 1.09861229 9.30565055 -#> Ag Au_INAA B Br_INAA Ca_INAA Co_INAA -#> -6.90775528 -6.21460810 1.09861229 0.09531018 9.21034037 1.09861229 -#> Cs_INAA Hg Hg_INAA K Ag Au_INAA -#> 0.00000000 -3.91202301 0.00000000 5.29831737 -2.12863179 -0.01918282 -#> B Br_INAA Ca_INAA Co_INAA Cs_INAA Hg -#> 2.39789527 4.02535169 11.00209984 4.04305127 2.07944154 -1.83258146 -#> Hg_INAA K -#> 1.09861229 9.30565055 -#> Ag As B Br_INAA Ca_INAA Co_INAA -#> -6.90775528 -2.30258509 1.09861229 0.09531018 9.21034037 1.09861229 -#> Cs_INAA Hg Hg_INAA K Ag As -#> 0.00000000 -3.91202301 0.00000000 5.29831737 -2.12863179 3.42426265 -#> B Br_INAA Ca_INAA Co_INAA Cs_INAA Hg -#> 2.39789527 4.02535169 11.00209984 4.04305127 2.07944154 -1.83258146 -#> Hg_INAA K -#> 1.09861229 9.30565055 -#> Ag As Au_INAA Br_INAA Ca_INAA Co_INAA -#> -6.90775528 -2.30258509 -6.21460810 0.09531018 9.21034037 1.09861229 -#> Cs_INAA Hg Hg_INAA K Ag As -#> 0.00000000 -3.91202301 0.00000000 5.29831737 -2.12863179 3.42426265 -#> Au_INAA Br_INAA Ca_INAA Co_INAA Cs_INAA Hg -#> -0.01918282 4.02535169 11.00209984 4.04305127 2.07944154 -1.83258146 -#> Hg_INAA K -#> 1.09861229 9.30565055 -#> Ag As Au_INAA B Ca_INAA Co_INAA -#> -6.90775528 -2.30258509 -6.21460810 1.09861229 9.21034037 1.09861229 -#> Cs_INAA Hg Hg_INAA K Ag As -#> 0.00000000 -3.91202301 0.00000000 5.29831737 -2.12863179 3.42426265 -#> Au_INAA B Ca_INAA Co_INAA Cs_INAA Hg -#> -0.01918282 2.39789527 11.00209984 4.04305127 2.07944154 -1.83258146 -#> Hg_INAA K -#> 1.09861229 9.30565055 -#> Ag As Au_INAA B Br_INAA Co_INAA -#> -6.90775528 -2.30258509 -6.21460810 1.09861229 0.09531018 1.09861229 -#> Cs_INAA Hg Hg_INAA K Ag As -#> 0.00000000 -3.91202301 0.00000000 5.29831737 -2.12863179 3.42426265 -#> Au_INAA B Br_INAA Co_INAA Cs_INAA Hg -#> -0.01918282 2.39789527 4.02535169 4.04305127 2.07944154 -1.83258146 -#> Hg_INAA K -#> 1.09861229 9.30565055 -#> Ag As Au_INAA B Br_INAA Ca_INAA -#> -6.90775528 -2.30258509 -6.21460810 1.09861229 0.09531018 9.21034037 -#> Cs_INAA Hg Hg_INAA K Ag As -#> 0.00000000 -3.91202301 0.00000000 5.29831737 -2.12863179 3.42426265 -#> Au_INAA B Br_INAA Ca_INAA Cs_INAA Hg -#> -0.01918282 2.39789527 4.02535169 11.00209984 2.07944154 -1.83258146 -#> Hg_INAA K -#> 1.09861229 9.30565055 -#> Ag As Au_INAA B Br_INAA Ca_INAA -#> -6.90775528 -2.30258509 -6.21460810 1.09861229 0.09531018 9.21034037 -#> Co_INAA Hg Hg_INAA K Ag As -#> 1.09861229 -3.91202301 0.00000000 5.29831737 -2.12863179 3.42426265 -#> Au_INAA B Br_INAA Ca_INAA Co_INAA Hg -#> -0.01918282 2.39789527 4.02535169 11.00209984 4.04305127 -1.83258146 -#> Hg_INAA K -#> 1.09861229 9.30565055 -#> Ag As Au_INAA B Br_INAA Ca_INAA -#> -6.90775528 -2.30258509 -6.21460810 1.09861229 0.09531018 9.21034037 -#> Co_INAA Cs_INAA Hg_INAA K Ag As -#> 1.09861229 0.00000000 0.00000000 5.29831737 -2.12863179 3.42426265 -#> Au_INAA B Br_INAA Ca_INAA Co_INAA Cs_INAA -#> -0.01918282 2.39789527 4.02535169 11.00209984 4.04305127 2.07944154 -#> Hg_INAA K -#> 1.09861229 9.30565055 -#> Ag As Au_INAA B Br_INAA Ca_INAA -#> -6.90775528 -2.30258509 -6.21460810 1.09861229 0.09531018 9.21034037 -#> Co_INAA Cs_INAA Hg K Ag As -#> 1.09861229 0.00000000 -3.91202301 5.29831737 -2.12863179 3.42426265 -#> Au_INAA B Br_INAA Ca_INAA Co_INAA Cs_INAA -#> -0.01918282 2.39789527 4.02535169 11.00209984 4.04305127 2.07944154 -#> Hg K -#> -1.83258146 9.30565055 -#> Ag As Au_INAA B Br_INAA Ca_INAA -#> -6.90775528 -2.30258509 -6.21460810 1.09861229 0.09531018 9.21034037 -#> Co_INAA Cs_INAA Hg Hg_INAA Ag As -#> 1.09861229 0.00000000 -3.91202301 0.00000000 -2.12863179 3.42426265 -#> Au_INAA B Br_INAA Ca_INAA Co_INAA Cs_INAA -#> -0.01918282 2.39789527 4.02535169 11.00209984 4.04305127 2.07944154 -#> Hg Hg_INAA -#> -1.83258146 1.09861229
@@ -364,15 +276,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/prepare.html b/reference/prepare.html index ab7cd72..dc37598 100644 --- a/reference/prepare.html +++ b/reference/prepare.html @@ -4,7 +4,7 @@ - +
- +

Transformation and standardization

- Source: R/prepare.R + Source: R/prepare.R
@@ -91,49 +91,49 @@

Transformation and standardization

Arguments

-
x
+ + +
x

a vector, matrix or data.frame.

-
scaling
+
scaling

the scaling to be applied to the data. Possible values are "none", "classical", MCD, "robust" and "onestep".

-
transformation
+
transformation

the transformation of the data. Possible values are "none", "minus", "reciprocal", "logarithm", "exponential", "boxcox", "clr", "ilr" and "alr".

-
alpha
+
alpha

a numeric parameter controlling the size of the subset for the MCD (if scaling="MCD"). See robustbase::covMcd().

-
powers
+
powers

a numeric vector giving the powers to be used in the Box-Cox transformation (if transformation="boxcox"). If NULL, the powers are calculated with function car::powerTransform().

-
start
+
start

a constant to be added prior to Box-Cox transformation (if transformation="boxcox").

-
alrVar
+
alrVar

variable to be used as denominator in the additive logratio transformation (if transformation="alr").

Value

- - -

Transformed and standardized data.

+

Transformed and standardized data.

Details

@@ -248,15 +248,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/pulplignin.html b/reference/pulplignin.html index 45cee5d..0f944ab 100644 --- a/reference/pulplignin.html +++ b/reference/pulplignin.html @@ -3,7 +3,7 @@ - +
- +

Pulp lignin content

- Source: R/VIM-package.R + Source: R/VIM-package.R
@@ -145,15 +145,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/rangerImpute.html b/reference/rangerImpute.html index 19b6a37..cc939b4 100644 --- a/reference/rangerImpute.html +++ b/reference/rangerImpute.html @@ -3,7 +3,7 @@ - +
- +

Random Forest Imputation

- Source: R/rangerImpute.R + Source: R/rangerImpute.R
@@ -88,47 +88,47 @@

Random Forest Imputation

Arguments

-
formula
+ + +
formula

model formula for the imputation

-
data
+
data

A data.frame containing the data

-
imp_var
+
imp_var

TRUE/FALSE if a TRUE/FALSE variables for each imputed variable should be created show the imputation status

-
imp_suffix
+
imp_suffix

suffix used for TF imputation variables

-
...
+
...

Arguments passed to ranger::ranger()

-
verbose
+
verbose

Show the number of observations used for training and evaluating the RF-Model. This parameter is also passed down to ranger::ranger() to show computation status.

-
median
+
median

Use the median (rather than the arithmetic mean) to average the values of individual trees for a more robust estimate.

Value

- - -

the imputed data set.

+

the imputed data set.

See also

-

Other imputation methods: +

Other imputation methods: hotdeck(), impPCA(), irmi(), @@ -284,15 +284,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/regressionImp.html b/reference/regressionImp.html index b0bd42b..db69c43 100644 --- a/reference/regressionImp.html +++ b/reference/regressionImp.html @@ -3,7 +3,7 @@ - +
- +

Regression Imputation

- Source: R/regressionImp.R + Source: R/regressionImp.R
@@ -88,33 +88,35 @@

Regression Imputation

Arguments

-
formula
+ + +
formula

model formula to impute one variable

-
data
+
data

A data.frame containing the data

-
family
+
family

family argument for glm(). "AUTO" (the default) tries to choose automatically and is the only really tested option!!!

-
robust
+
robust

TRUE/FALSE if robust regression should be used. See details.

-
imp_var
+
imp_var

TRUE/FALSE if a TRUE/FALSE variables for each imputed variable should be created show the imputation status

-
imp_suffix
+
imp_suffix

suffix used for TF imputation variables

-
mod_cat
+
mod_cat

TRUE/FALSE if TRUE for categorical variables the level with the highest prediction probability is selected, otherwise it is sampled according to the probabilities.

@@ -122,9 +124,7 @@

Arguments

Value

- - -

the imputed data set.

+

the imputed data set.

Details

@@ -139,7 +139,7 @@

References

See also

-

Other imputation methods: +

Other imputation methods: hotdeck(), impPCA(), irmi(), @@ -182,15 +182,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/rugNA.html b/reference/rugNA.html index a71595b..8613cce 100644 --- a/reference/rugNA.html +++ b/reference/rugNA.html @@ -4,7 +4,7 @@ - +
- +

Rug representation of missing/imputed values

- Source: R/rugNA.R + Source: R/rugNA.R
@@ -92,29 +92,31 @@

Rug representation of missing/imputed values

Arguments

-
x, y
+ + +
x, y

numeric vectors.

-
ticksize
+
ticksize

the length of the ticks. Positive lengths give inward ticks.

-
side
+
side

an integer giving the side of the plot to draw the rug representation.

-
col
+
col

the color to be used for the ticks.

-
alpha
+
alpha

the alpha value (between 0 and 1).

-
miss
+
miss

a data.frame or matrix with two columns and logical values. If NULL, x and y are searched for missing values, otherwise, the first column of miss is used to @@ -122,11 +124,11 @@

Arguments

values in y.

-
lwd
+
lwd

the line width to be used for the ticks.

-
...
+
...

further arguments to be passed to graphics::Axis().

@@ -156,10 +158,6 @@

Examples

## for imputed values x_imp <- kNN(tao[, c("Air.Temp","Humidity")]) -#> Humidity Humidity -#> 71.6 94.8 -#> Air.Temp Air.Temp -#> 21.42 28.50 x <- x_imp[, "Air.Temp"] y <- x_imp[, "Humidity"] miss <- x_imp[, c("Air.Temp_imp","Humidity_imp")] @@ -182,15 +180,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/sampleCat.html b/reference/sampleCat.html index a68a2f3..365fc49 100644 --- a/reference/sampleCat.html +++ b/reference/sampleCat.html @@ -4,7 +4,7 @@ - +
- +

Random aggregation function for a factor variable

- Source: R/sampleCat.R + Source: R/sampleCat.R
@@ -82,17 +82,19 @@

Random aggregation function for a factor variable

Arguments

-
x
+ + +
x

factor vector

-
weights
+
weights

numeric vector providing weights for the observations in x

See also

-

Other imputation methods: +

Other imputation methods: hotdeck(), impPCA(), irmi(), @@ -116,15 +118,15 @@

See also

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/scattJitt.html b/reference/scattJitt.html index 0d40f57..9f0155c 100644 --- a/reference/scattJitt.html +++ b/reference/scattJitt.html @@ -3,7 +3,7 @@ - +
- +

Bivariate jitter plot

- Source: R/scattJitt.R + Source: R/scattJitt.R
@@ -99,11 +99,13 @@

Bivariate jitter plot

Arguments

-
x
+ + +
x

a data.frame or matrix with two columns.

-
delimiter
+
delimiter

a character-vector to distinguish between variables and imputation-indices for imputed variables (therefore, x needs to have colnames()). If given, it is used to determine the corresponding @@ -113,7 +115,7 @@

Arguments

to the given colors for imputed variables (see col).

-
col
+
col

a vector of length five giving the colors to be used in the plot. The first color will be used for complete observations, the second/fourth color for missing/imputed values in only one variable, and the third/fifth @@ -122,64 +124,64 @@

Arguments

one is recycled.

-
alpha
+
alpha

a numeric value between 0 and 1 giving the level of transparency of the colors, or NULL. This can be used to prevent overplotting.

-
cex
+
cex

the character expansion factor for the plot characters.

-
col.line
+
col.line

the color for the lines dividing the plot region.

-
lty
+
lty

the line type for the lines dividing the plot region (see graphics::par()).

-
lwd
+
lwd

the line width for the lines dividing the plot region.

-
numbers
+
numbers

a logical indicating whether the frequencies of observed and missing/imputed values should be displayed (see ‘Details’).

-
cex.numbers
+
cex.numbers

the character expansion factor to be used for the frequencies of the observed and missing/imputed values.

-
main, sub
+
main, sub

main and sub title.

-
xlab, ylab
+
xlab, ylab

axis labels.

-
axes
+
axes

a logical indicating whether both axes should be drawn on the plot. Use graphical parameter "xaxt" or "yaxt" to suppress just one of the axes.

-
frame.plot
+
frame.plot

a logical indicating whether a box should be drawn around the plot.

-
labels
+
labels

a vector of length three giving the axis labels for the regions for observed, missing and imputed values (see ‘Details’).

-
...
+
...

further graphical parameters to be passed down (see graphics::par()).

@@ -209,7 +211,7 @@

References

See also

-

Other plotting functions: +

Other plotting functions: aggr(), barMiss(), histMiss(), @@ -239,10 +241,6 @@

Examples

## for imputed values scattJitt(kNN(tao[, c("Air.Temp", "Humidity")]), delimiter = "_imp") -#> Humidity Humidity -#> 71.6 94.8 -#> Air.Temp Air.Temp -#> 21.42 28.50
@@ -259,15 +257,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/scattMiss.html b/reference/scattMiss.html index bd00f31..b90588a 100644 --- a/reference/scattMiss.html +++ b/reference/scattMiss.html @@ -5,7 +5,7 @@ - +
- +

Scatterplot with information about missing/imputed values

- Source: R/scattMiss.R + Source: R/scattMiss.R
@@ -103,11 +103,13 @@

Scatterplot with information about missing/imputed values

Arguments

-
x
+ + +
x

a matrix or data.frame with two columns.

-
delimiter
+
delimiter

a character-vector to distinguish between variables and imputation-indices for imputed variables (therefore, x needs to have colnames()). If given, it is used to determine the corresponding @@ -117,14 +119,14 @@

Arguments

to the given colors for imputed variables (see col).

-
side
+
side

if side=1, a rug representation and vertical lines are plotted for the missing/imputed values in the second variable; if side=2, a rug representation and horizontal lines for the missing/imputed values in the first variable.

-
col
+
col

a vector of length four giving the colors to be used in the plot. The first color is used for the scatterplot, the second/third color for the rug representation for missing/imputed values. The second color is also used @@ -136,34 +138,34 @@

Arguments

default color is used for the ellipses as well.

-
alpha
+
alpha

a numeric value between 0 and 1 giving the level of transparency of the colors, or NULL. This can be used to prevent overplotting.

-
lty
+
lty

a vector of length two giving the line types for the lines and ellipses. If a single value is supplied, it will be used for both.

-
lwd
+
lwd

a vector of length two giving the line widths for the lines and ellipses. If a single value is supplied, it will be used for both.

-
quantiles
+
quantiles

a vector giving the quantiles of the chi-square distribution to be used for the tolerance ellipses, or NULL to suppress plotting ellipses (see ‘Details’).

-
inEllipse
+
inEllipse

plot lines only inside the largest ellipse. Ignored if quantiles is NULL or if there are imputed values.

-
zeros
+
zeros

a logical vector of length two indicating whether the variables are semi-continuous, i.e., contain a considerable amount of zeros. If TRUE, only the non-zero observations are used for computing the @@ -171,24 +173,24 @@

Arguments

Ignored if quantiles is NULL.

-
xlim, ylim
+
xlim, ylim

axis limits.

-
main, sub
+
main, sub

main and sub title.

-
xlab, ylab
+
xlab, ylab

axis labels.

-
interactive
+
interactive

a logical indicating whether the side argument can be changed interactively (see ‘Details’).

-
...
+
...

further graphical parameters to be passed down (see graphics::par()).

@@ -221,7 +223,7 @@

References

See also

marginplot()

-

Other plotting functions: +

Other plotting functions: aggr(), barMiss(), histMiss(), @@ -251,10 +253,6 @@

Examples

## for imputed values scattMiss(kNN(tao[,c("Air.Temp", "Humidity")]), delimiter = "_imp") -#> Humidity Humidity -#> 71.6 94.8 -#> Air.Temp Air.Temp -#> 21.42 28.50
@@ -271,15 +269,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/scattmatrixMiss.html b/reference/scattmatrixMiss.html index ae9e672..ed7d228 100644 --- a/reference/scattmatrixMiss.html +++ b/reference/scattmatrixMiss.html @@ -4,7 +4,7 @@ - +
- +

Scatterplot matrix with information about missing/imputed values

- Source: R/scattmatrixMiss.R + Source: R/scattmatrixMiss.R
@@ -95,11 +95,13 @@

Scatterplot matrix with information about missing/imputed values

Arguments

-
x
+ + +
x

a matrix or data.frame.

-
delimiter
+
delimiter

a character-vector to distinguish between variables and imputation-indices for imputed variables (therefore, x needs to have colnames()). If given, it is used to determine the corresponding @@ -109,12 +111,12 @@

Arguments

to the given colors for imputed variables (see col).

-
highlight
+
highlight

a vector giving the variables to be used for highlighting. If NULL (the default), all variables are used for highlighting.

-
selection
+
selection

the selection method for highlighting missing/imputed values in multiple highlight variables. Possible values are "any" (highlighting of missing/imputed values in any of the highlight @@ -122,47 +124,47 @@

Arguments

all of the highlight variables).

-
plotvars
+
plotvars

a vector giving the variables to be plotted. If NULL (the default), all variables are plotted.

-
col
+
col

a vector of length three giving the colors to be used in the plot. The second/third color will be used for highlighting missing/imputed values.

-
alpha
+
alpha

a numeric value between 0 and 1 giving the level of transparency of the colors, or NULL. This can be used to prevent overplotting.

-
pch
+
pch

a vector of length two giving the plot characters. The second plot character will be used for the highlighted observations.

-
lty
+
lty

a vector of length two giving the line types for the density plots in the diagonal panels (if diagonal="density"). The second line type is used for the highlighted observations. If a single value is supplied, it is used for both non-highlighted and highlighted observations.

-
diagonal
+
diagonal

a character string specifying the plot to be drawn in the diagonal panels. Possible values are "density" (density plots for non-highlighted and highlighted observations) and "none".

-
interactive
+
interactive

a logical indicating whether the variables to be used for highlighting can be selected interactively (see ‘Details’).

-
...
+
...

for scattmatrixMiss, further arguments and graphical parameters to be passed to pairsVIM(). par("oma") will be set appropriately unless supplied (see graphics::par()). For @@ -207,7 +209,7 @@

References

See also

pairsVIM(), marginmatrix()

-

Other plotting functions: +

Other plotting functions: aggr(), barMiss(), histMiss(), @@ -240,12 +242,6 @@

Examples

## for imputed values x_imp <- kNN(sleep[, 1:5]) -#> BodyWgt BrainWgt Dream Sleep BodyWgt BrainWgt Dream Sleep -#> 0.005 0.140 0.000 2.600 6654.000 5712.000 6.600 19.900 -#> BodyWgt BrainWgt NonD Sleep BodyWgt BrainWgt NonD Sleep -#> 0.005 0.140 2.100 2.600 6654.000 5712.000 17.900 19.900 -#> BodyWgt BrainWgt NonD Dream BodyWgt BrainWgt NonD Dream -#> 0.005 0.140 2.100 0.000 6654.000 5712.000 17.900 6.600 x_imp[,c(1,2,4)] <- log10(x_imp[,c(1,2,4)]) scattmatrixMiss(x_imp, delimiter = "_imp", highlight = "Dream") #> Warning: variable 'Dream' contains infinite values @@ -265,15 +261,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/sleep.html b/reference/sleep.html index f940e16..09a0c22 100644 --- a/reference/sleep.html +++ b/reference/sleep.html @@ -3,7 +3,7 @@ - +
- +

Mammal sleep data

- Source: R/VIM-package.R + Source: R/VIM-package.R
@@ -102,12 +102,12 @@

Format

numeric vector

Danger

a numeric vector

- +

Source

Allison, T. and Chichetti, D. (1976) Sleep in mammals: ecological -and constitutional correlates. Science 194 (4266), 732--734.

+and constitutional correlates. Science 194 (4266), 732–734.

The data set was imported from GGobi.

@@ -157,15 +157,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/spineMiss.html b/reference/spineMiss.html index 2b2e29f..060583d 100644 --- a/reference/spineMiss.html +++ b/reference/spineMiss.html @@ -6,7 +6,7 @@ - +
- +

Spineplot with information about missing/imputed values

- Source: R/spineMiss.R + Source: R/spineMiss.R
@@ -105,11 +105,13 @@

Spineplot with information about missing/imputed values

Arguments

-
x
+ + +
x

a vector, matrix or data.frame.

-
delimiter
+
delimiter

a character-vector to distinguish between variables and imputation-indices for imputed variables (therefore, x needs to have colnames()). If given, it is used to determine the corresponding @@ -119,12 +121,12 @@

Arguments

to the given colors for imputed variables (see col).

-
pos
+
pos

a numeric value giving the index of the variable of interest. Additional variables in x are used for highlighting.

-
selection
+
selection

the selection method for highlighting missing/imputed values in multiple additional variables. Possible values are "any" (highlighting of missing/imputed values in any of the additional @@ -132,75 +134,73 @@

Arguments

all of the additional variables).

-
breaks
+
breaks

if the variable of interest is numeric, breaks controls the breakpoints (see graphics::hist() for possible values).

-
right
+
right

logical; if TRUE and the variable of interest is numeric, the spinogram cells are right-closed (left-open) intervals.

-
col
+
col

a vector of length six giving the colors to be used. If only one color is supplied, the bars are transparent and the supplied color is used for highlighting missing/imputed values. Else if two colors are supplied, they are recycled.

-
border
+
border

the color to be used for the border of the cells. Use border=NA to omit borders.

-
main, sub
+
main, sub

main and sub title.

-
xlab, ylab
+
xlab, ylab

axis labels.

-
axes
+
axes

a logical indicating whether axes should be drawn on the plot.

-
labels
+
labels

if the variable of interest is categorical, either a logical indicating whether labels should be plotted below each cell, or a character vector giving the labels. This is ignored if the variable of interest is numeric.

-
only.miss
+
only.miss

logical; if TRUE, the missing/imputed values in the variable of interest are also visualized by a cell in the spineplot or spinogram. Otherwise, a small spineplot is drawn on the right hand side (see ‘Details’).

-
miss.labels
+
miss.labels

either a logical indicating whether label(s) should be plotted below the cell(s) on the right hand side, or a character string or vector giving the label(s) (see ‘Details’).

-
interactive
+
interactive

a logical indicating whether the variables can be switched interactively (see ‘Details’).

-
...
+
...

further graphical parameters to be passed to graphics::title() and graphics::axis().

Value

- - -

a table containing the frequencies corresponding to the cells.

+

a table containing the frequencies corresponding to the cells.

Details

@@ -251,7 +251,7 @@

References

See also

histMiss(), barMiss(), mosaicMiss()

-

Other plotting functions: +

Other plotting functions: aggr(), barMiss(), histMiss(), @@ -284,14 +284,8 @@

Examples

## for imputed values spineMiss(kNN(tao[, c("Air.Temp", "Humidity")]), delimiter = "_imp") -#> Humidity Humidity -#> 71.6 94.8 -#> Air.Temp Air.Temp -#> 21.42 28.50 spineMiss(kNN(sleep[, c("Exp", "Sleep")]), delimiter = "_imp") -#> Exp Exp -#> 1 5
@@ -308,15 +302,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/tableMiss.html b/reference/tableMiss.html index 89e9476..6e16fe6 100644 --- a/reference/tableMiss.html +++ b/reference/tableMiss.html @@ -3,8 +3,8 @@ with the same colors as histMiss()"> - + +
- +

create table with highlighted missings/imputations

- Source: R/tableMiss.R + Source: R/tableMiss.R
@@ -82,11 +82,13 @@

create table with highlighted missings/imputations

Arguments

-
x
+ + +
x

a vector, matrix or data.frame.

-
delimiter
+
delimiter

a character-vector to distinguish between variables and imputation-indices for imputed variables (therefore, x needs to have colnames()). If given, it is used to determine the corresponding @@ -101,10 +103,6 @@

Arguments

Examples

data(tao)
 x_IMPUTED <- kNN(tao[, c("Air.Temp", "Humidity")])
-#> Humidity Humidity 
-#>     71.6     94.8 
-#> Air.Temp Air.Temp 
-#>    21.42    28.50 
 tableMiss(x_IMPUTED[105:114, ])
 

 x_IMPUTED[106, 2] <- NA
@@ -126,15 +124,15 @@ 
Examples
-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/tao.html b/reference/tao.html index 28b9dbc..fb93a20 100644 --- a/reference/tao.html +++ b/reference/tao.html @@ -4,7 +4,7 @@ - +
- +

Tropical Atmosphere Ocean (TAO) project data

- Source: R/VIM-package.R + Source: R/VIM-package.R
@@ -99,7 +99,7 @@

Format

zonal wind, i.e. latitude-parallel wind

VWind

meridional wind, i.e. longitude-parallel wind

- +

Source

@@ -148,15 +148,15 @@

Examples

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/reference/testdata.html b/reference/testdata.html index f6548ba..28a761d 100644 --- a/reference/testdata.html +++ b/reference/testdata.html @@ -3,7 +3,7 @@ - +
- +

Simulated data set for testing purpose

- Source: R/VIM-package.R + Source: R/VIM-package.R
@@ -86,7 +86,7 @@

Format

  • m1: numeric 0 8.29 9.08 0 0 ...

  • m2: numeric 10.66 9.39 7.8 8.11 7.33 ...

    • -

  • $wona : a `data.frame`` with 500 obs. of 8 variables:

    • x1: numeric 10.87 9.53 7.83 8.53 8.67 ...

      • +

    • $wona : a `data.frame“ with 500 obs. of 8 variables:

      • x1: numeric 10.87 9.53 7.83 8.53 8.67 ...

      • x2: numeric 10.9 9.32 7.68 8.2 8.41 ...

      • c1: Factor w/ 4 levels "a","b","c","d": 3 2 2 1 2 2 1 3 3 2 ...

      • c2: Factor w/ 4 levels "a","b","c","d": 2 3 2 2 2 2 2 4 2 2 ...

        • @@ -96,7 +96,7 @@

        Format

      • m2: numeric 10.66 9.39 7.8 8.11 7.33 ...

    • $mixed: c("m1", "m2")

      • -

    • $outlierInd: `NULL``

      • +

    • $outlierInd: `NULL“

    • @@ -118,15 +118,15 @@

    Examples

    -

    Site built with pkgdown 2.0.9.

    +

    Site built with pkgdown 2.1.0.

    - - + + diff --git a/reference/toydataMiss.html b/reference/toydataMiss.html index cee0995..9f0e07c 100644 --- a/reference/toydataMiss.html +++ b/reference/toydataMiss.html @@ -3,7 +3,7 @@ - +
    - +

    Simulated toy data set for examples

    - Source: R/VIM-package.R + Source: R/VIM-package.R
    @@ -100,15 +100,15 @@

    Examples

    -

    Site built with pkgdown 2.0.9.

    +

    Site built with pkgdown 2.1.0.

    - - + + diff --git a/reference/wine.html b/reference/wine.html index 33d7e2e..b687bc0 100644 --- a/reference/wine.html +++ b/reference/wine.html @@ -3,7 +3,7 @@ - +
    - +

    Wine tasting and price

    - Source: R/VIM-package.R + Source: R/VIM-package.R
    @@ -151,15 +151,15 @@

    Examples

    -

    Site built with pkgdown 2.0.9.

    +

    Site built with pkgdown 2.1.0.

    - - + + diff --git a/reference/xgboostImpute.html b/reference/xgboostImpute.html index 4007d1d..22fd043 100644 --- a/reference/xgboostImpute.html +++ b/reference/xgboostImpute.html @@ -3,7 +3,7 @@ - +
    - +

    Xgboost Imputation

    - Source: R/xgboostImpute.R + Source: R/xgboostImpute.R
    @@ -89,52 +89,52 @@

    Xgboost Imputation

    Arguments

    -
    formula
    + + +
    formula

    model formula for the imputation

    -
    data
    +
    data

    A data.frame containing the data

    -
    imp_var
    +
    imp_var

    TRUE/FALSE if a TRUE/FALSE variables for each imputed variable should be created show the imputation status

    -
    imp_suffix
    +
    imp_suffix

    suffix used for TF imputation variables

    -
    verbose
    +
    verbose

    Show the number of observations used for training and evaluating the RF-Model. This parameter is also passed down to xgboost::xgboost() to show computation status.

    -
    nrounds
    +
    nrounds

    max number of boosting iterations, argument passed to xgboost::xgboost()

    -
    objective
    +
    objective

    objective for xgboost, argument passed to xgboost::xgboost()

    -
    ...
    +
    ...

    Arguments passed to xgboost::xgboost()

    Value

    - - -

    the imputed data set.

    +

    the imputed data set.

    See also

    -

    Other imputation methods: +

    Other imputation methods: hotdeck(), impPCA(), irmi(), @@ -549,15 +549,15 @@

    Examples

    -

    Site built with pkgdown 2.0.9.

    +

    Site built with pkgdown 2.1.0.

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