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alexkowa committed Oct 25, 2014
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60 changes: 30 additions & 30 deletions DESCRIPTION
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Package: VIM
Version: 4.1.0
Date: 2014-10-24
Title: Visualization and Imputation of Missing Values
Author: Matthias Templ, Andreas Alfons, Alexander Kowarik, Bernd Prantner
Maintainer: Matthias Templ <[email protected]>
Depends:
R (>= 3.1.0),colorspace,grid,data.table(>= 1.9.4)
Imports:
car,
grDevices,
robustbase,
stats,
sp,
vcd,MASS,nnet,e1071,methods,Rcpp
Description: This package introduces new tools for the visualization of missing
and/or imputed values, which can be used for exploring the data and the
structure of the missing and/or imputed values. Depending on this structure
of the missing values, the corresponding methods may help to identify the
mechanism generating the missing values and allows to explore the data
including missing values. In addition, the quality of imputation can be
visually explored using various univariate, bivariate, multiple and
multivariate plot methods. A graphical user interface available in the
separate package VIMGUI allows an easy handling of the implemented plot
methods.
LazyData: TRUE
License: GPL (>= 2)
URL: https://github.com/alexkowa/VIM
Repository: CRAN
LinkingTo: Rcpp
Package: VIM
Version: 4.1.0
Date: 2014-10-24
Title: Visualization and Imputation of Missing Values
Author: Matthias Templ, Andreas Alfons, Alexander Kowarik, Bernd Prantner
Maintainer: Matthias Templ <[email protected]>
Depends:
R (>= 3.1.0),colorspace,grid,data.table(>= 1.9.4)
Imports:
car,
grDevices,
robustbase,
stats,
sp,
vcd,MASS,nnet,e1071,methods,Rcpp
Description: This package introduces new tools for the visualization of missing
and/or imputed values, which can be used for exploring the data and the
structure of the missing and/or imputed values. Depending on this structure
of the missing values, the corresponding methods may help to identify the
mechanism generating the missing values and allows to explore the data
including missing values. In addition, the quality of imputation can be
visually explored using various univariate, bivariate, multiple and
multivariate plot methods. A graphical user interface available in the
separate package VIMGUI allows an easy handling of the implemented plot
methods.
LazyData: TRUE
License: GPL (>= 2)
URL: https://github.com/alexkowa/VIM
Repository: CRAN
LinkingTo: Rcpp
232 changes: 116 additions & 116 deletions NAMESPACE
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# Generated by roxygen2 (4.0.2): do not edit by hand
S3method(aggr,data.frame)
S3method(aggr,default)
S3method(aggr,survey.design)
S3method(barMiss,data.frame)
S3method(barMiss,default)
S3method(barMiss,survey.design)
S3method(colormapMiss,data.frame)
S3method(colormapMiss,default)
S3method(colormapMiss,survey.design)
S3method(growdotMiss,data.frame)
S3method(growdotMiss,default)
S3method(growdotMiss,survey.design)
S3method(histMiss,data.frame)
S3method(histMiss,default)
S3method(histMiss,survey.design)
S3method(hotdeck,data.frame)
S3method(hotdeck,default)
S3method(hotdeck,survey.design)
S3method(irmi,data.frame)
S3method(irmi,default)
S3method(irmi,survey.design)
S3method(kNN,data.frame)
S3method(kNN,default)
S3method(kNN,survey.design)
S3method(mapMiss,data.frame)
S3method(mapMiss,default)
S3method(mapMiss,survey.design)
S3method(marginmatrix,data.frame)
S3method(marginmatrix,default)
S3method(marginmatrix,survey.design)
S3method(matrixplot,data.frame)
S3method(matrixplot,default)
S3method(matrixplot,survey.design)
S3method(mosaicMiss,data.frame)
S3method(mosaicMiss,default)
S3method(mosaicMiss,survey.design)
S3method(parcoordMiss,data.frame)
S3method(parcoordMiss,default)
S3method(parcoordMiss,survey.design)
S3method(pbox,data.frame)
S3method(pbox,default)
S3method(pbox,survey.design)
S3method(plot,aggr)
S3method(prepare,data.frame)
S3method(prepare,default)
S3method(prepare,survey.design)
S3method(print,aggr)
S3method(print,summary.aggr)
S3method(regressionImp,data.frame)
S3method(regressionImp,default)
S3method(regressionImp,survey.design)
S3method(scattmatrixMiss,data.frame)
S3method(scattmatrixMiss,default)
S3method(scattmatrixMiss,survey.design)
S3method(summary,aggr)
export(aggr)
export(alphablend)
export(barMiss)
export(bgmap)
export(colSequence)
export(colSequenceHCL)
export(colSequenceRGB)
export(colormapMiss)
export(colormapMissLegend)
export(countInf)
export(countNA)
export(existsVm)
export(getVm)
export(gowerD)
export(growdotMiss)
export(histMiss)
export(hotdeck)
export(initialise)
export(irmi)
export(kNN)
export(mapMiss)
export(marginmatrix)
export(marginplot)
export(matrixplot)
export(maxCat)
export(mosaicMiss)
export(pairsVIM)
export(parcoordMiss)
export(pbox)
export(plot.aggr)
export(prepare)
export(putVm)
export(regressionImp)
export(rmVm)
export(rugNA)
export(sampleCat)
export(scattJitt)
export(scattMiss)
export(scattmatrixMiss)
export(spineMiss)
export(vmGUIenvir)
export(which.minN)
import(MASS)
import(Rcpp)
import(colorspace)
import(data.table)
import(e1071)
import(grDevices)
import(grid)
import(methods)
import(nnet)
import(robustbase)
import(sp)
import(stats)
importFrom(car,bcPower)
importFrom(car,powerTransform)
importFrom(vcd,labeling_border)
importFrom(vcd,mosaic)
useDynLib(VIM)
# Generated by roxygen2 (4.0.2): do not edit by hand

S3method(aggr,data.frame)
S3method(aggr,default)
S3method(aggr,survey.design)
S3method(barMiss,data.frame)
S3method(barMiss,default)
S3method(barMiss,survey.design)
S3method(colormapMiss,data.frame)
S3method(colormapMiss,default)
S3method(colormapMiss,survey.design)
S3method(growdotMiss,data.frame)
S3method(growdotMiss,default)
S3method(growdotMiss,survey.design)
S3method(histMiss,data.frame)
S3method(histMiss,default)
S3method(histMiss,survey.design)
S3method(hotdeck,data.frame)
S3method(hotdeck,default)
S3method(hotdeck,survey.design)
S3method(irmi,data.frame)
S3method(irmi,default)
S3method(irmi,survey.design)
S3method(kNN,data.frame)
S3method(kNN,default)
S3method(kNN,survey.design)
S3method(mapMiss,data.frame)
S3method(mapMiss,default)
S3method(mapMiss,survey.design)
S3method(marginmatrix,data.frame)
S3method(marginmatrix,default)
S3method(marginmatrix,survey.design)
S3method(matrixplot,data.frame)
S3method(matrixplot,default)
S3method(matrixplot,survey.design)
S3method(mosaicMiss,data.frame)
S3method(mosaicMiss,default)
S3method(mosaicMiss,survey.design)
S3method(parcoordMiss,data.frame)
S3method(parcoordMiss,default)
S3method(parcoordMiss,survey.design)
S3method(pbox,data.frame)
S3method(pbox,default)
S3method(pbox,survey.design)
S3method(plot,aggr)
S3method(prepare,data.frame)
S3method(prepare,default)
S3method(prepare,survey.design)
S3method(print,aggr)
S3method(print,summary.aggr)
S3method(regressionImp,data.frame)
S3method(regressionImp,default)
S3method(regressionImp,survey.design)
S3method(scattmatrixMiss,data.frame)
S3method(scattmatrixMiss,default)
S3method(scattmatrixMiss,survey.design)
S3method(summary,aggr)
export(aggr)
export(alphablend)
export(barMiss)
export(bgmap)
export(colSequence)
export(colSequenceHCL)
export(colSequenceRGB)
export(colormapMiss)
export(colormapMissLegend)
export(countInf)
export(countNA)
export(existsVm)
export(getVm)
export(gowerD)
export(growdotMiss)
export(histMiss)
export(hotdeck)
export(initialise)
export(irmi)
export(kNN)
export(mapMiss)
export(marginmatrix)
export(marginplot)
export(matrixplot)
export(maxCat)
export(mosaicMiss)
export(pairsVIM)
export(parcoordMiss)
export(pbox)
export(plot.aggr)
export(prepare)
export(putVm)
export(regressionImp)
export(rmVm)
export(rugNA)
export(sampleCat)
export(scattJitt)
export(scattMiss)
export(scattmatrixMiss)
export(spineMiss)
export(vmGUIenvir)
export(which.minN)
import(MASS)
import(Rcpp)
import(colorspace)
import(data.table)
import(e1071)
import(grDevices)
import(grid)
import(methods)
import(nnet)
import(robustbase)
import(sp)
import(stats)
importFrom(car,bcPower)
importFrom(car,powerTransform)
importFrom(vcd,labeling_border)
importFrom(vcd,mosaic)
useDynLib(VIM)
4 changes: 2 additions & 2 deletions R/hotdeck.R
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#' @param makeNA list of length equal to the number of variables, with values, that should be converted to NA for each variable
#' @param NAcond list of length equal to the number of variables, with a condition for imputing a NA
#' @param impNA TRUE/FALSE whether NA should be imputed
#' @param list of length equal to the number of variables, with a donorcond condition for the donors e.g. ">5"
#' @param donorcond list of length equal to the number of variables, with a donorcond condition for the donors e.g. ">5"
#' @param imp_var TRUE/FALSE if a TRUE/FALSE variables for each imputed
#' variable should be created show the imputation status
#' @param imp_suffix suffix for the TRUE/FALSE variables showing the imputation
Expand All @@ -46,7 +46,7 @@
#' nRows <- 1e3
#' # Generate a data set with nRows rows and several variables
#' x<-data.frame(x=rnorm(nRows),y=rnorm(nRows),z=sample(LETTERS,nRows,replace=TRUE),
#' d1=sample(LETTERS[1:3],nRows,rep=T),d2=sample(LETTERS[1:2],nRows,replace=TRUE),
#' d1=sample(LETTERS[1:3],nRows,replace=TRUE),d2=sample(LETTERS[1:2],nRows,replace=TRUE),
#' o1=rnorm(nRows),o2=rnorm(nRows),o3=rnorm(100))
#' origX <- x
#' x[sample(1:nRows,nRows/10),1] <- NA
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