Merge branch 'develop-0.5.7'

DESCRIPTION

@@ -2,7 +2,7 @@ Package: ggpmisc
 Type: Package
 Title: Miscellaneous Extensions to 'ggplot2'
 Version: 0.5.6.9003
-Date: 2024-05-26
+Date: 2024-06-01
 Authors@R:
     c(
     person("Pedro J.", "Aphalo", email = "[email protected]", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-3385-972X")),

NEWS.md

@@ -14,6 +14,7 @@ editor_options:
 -   Export the new utility functions now used internally for formatting parameter estimates into character strings in `stat_poly_eq()`, `stat_ma_eq()`, `stat_quant_eq()`, `stat_correlation()`, and `stat_multcomp()`.
 -   Implement R options `ggpmisc.small.p`, `ggpmisc.small.r` and `ggpmisc.decreasing.poly.eq`.
 -   Allow user-defined fit methods passed as argument to `stat_poly_eq()`, `stat_poly_line()`, `stat_ma_eq()`, `stat_ma_line()`, `stat_quant_eq()`, `stat_quant_line()`, and `stat_quant_band()` to return an atomic `NA` or a length zero object to skip labelling or plotting related to the attempted model fit.
+-   Implement automatic switch to `output.type = "markdown"` for `geom = "marquee"`.
 
 # ggpmisc 0.5.6
 

R/stat-correlation.R

@@ -286,7 +286,7 @@ stat_correlation <-
            show.legend = FALSE,
            inherit.aes = TRUE) {
     if (is.null(output.type)) {
-      if (geom %in% c("richtext", "textbox")) {
+      if (geom %in% c("richtext", "textbox", "marquee")) {
         output.type <- "markdown"
       } else {
         output.type <- "expression"
@@ -465,6 +465,7 @@ cor_test_compute_fun <- function(data,
   z[["n"]] <- nrow(na.omit(data[ , c("x", "y")]))
   z[["method"]] <- method
   z[["r.conf.level"]] <- conf.level
+
   if (boot.R >= 50 && conf.level > 0) {
     confint.boot <-
       confintr::ci_cor(data[ , c("x", "y")],
@@ -479,8 +480,8 @@ cor_test_compute_fun <- function(data,
       z[["r.confint.low"]]  <-  htest.ls[["conf.int"]][1]
       z[["r.confint.high"]] <-  htest.ls[["conf.int"]][2]
     } else {
-      if (conf.level < 0) {
-        message("Skipping bootstrap estimation as 'conf.level' < 0")
+      if (conf.level <= 0) {
+        message("Skipping bootstrap estimation as 'conf.level' <= 0")
       } else if (boot.R > 0) {
         warning("Skipping bootstrap estimation as 'boot.R' < 50")
       }

R/stat-ma-eq.R

@@ -356,7 +356,7 @@ stat_ma_eq <- function(mapping = NULL, data = NULL,
   }
 
   if (is.null(output.type)) {
-    if (geom %in% c("richtext", "textbox")) {
+    if (geom %in% c("richtext", "textbox", "marquee")) {
       output.type <- "markdown"
     } else {
       output.type <- "expression"

R/stat-multcomp.R

@@ -378,7 +378,7 @@ stat_multcomp <- function(mapping = NULL, data = NULL,
   }
 
   if (is.null(output.type)) {
-    if (geom %in% c("richtext", "textbox")) {
+    if (geom %in% c("richtext", "textbox", "marquee")) {
       output.type <- "markdown"
     } else {
       output.type <- "expression"

R/stat-poly-eq.R

@@ -552,7 +552,7 @@ stat_poly_eq <- function(mapping = NULL, data = NULL,
   }
 
   if (is.null(output.type)) {
-    if (geom %in% c("richtext", "textbox")) {
+    if (geom %in% c("richtext", "textbox", "marquee")) {
       output.type <- "markdown"
     } else {
       output.type <- "expression"

inst-not/GLM/GLM-in-stat-poly_line.R

@@ -12,9 +12,23 @@ model <- glm(y ~ x, data = df, family = gaussian)
 
 ggplot(df, aes(x, y)) +
   geom_point() +
-  stat_poly_line(method = "glm", method.args = list(family = gaussian)) +
+  stat_poly_line(method = "lm", se = TRUE) +
+  stat_poly_eq(method = "lm")
+
+ggplot(df, aes(x, y)) +
+  geom_point() +
+  stat_poly_line(method = "glm", method.args = list(family = gaussian), se = FALSE) +
+  stat_poly_eq(use_label("eq"), method = "glm", method.args = list(family = gaussian))
+
+ggplot(df, aes(x, y)) +
+  geom_point() +
+  stat_smooth(method = "glm", method.args = list(family = gaussian), se = TRUE) +
   stat_poly_eq(method = "glm", method.args = list(family = gaussian))
 
+ggplot(df, aes(x, y)) +
+  geom_point() +
+  stat_poly_line(method = "glm", method.args = list(family = gaussian), se = TRUE) +
+  stat_poly_eq(use_label("eq", "p"), method = "glm", method.args = list(family = gaussian))
 
 # Poisson -> poisson ------------------------------------------------------
 # example from https://stackoverflow.com/questions/69808033/how-can-i-create-a-ggplot-with-a-regression-line-based-on-the-predicted-values-o
@@ -28,5 +42,10 @@ model <- glm(y ~ x, data = df, family = poisson)
 
 ggplot(df, aes(x, y)) +
   geom_point() +
-  stat_poly_line(method = "glm", method.args = list(family = poisson)) +
+  stat_poly_line(method = "glm", method.args = list(family = poisson), se = FALSE) +
+  stat_poly_eq(method = "glm", method.args = list(family = poisson))
+
+ggplot(df, aes(x, y)) +
+  geom_point() +
+  stat_smooth(method = "glm", method.args = list(family = poisson), se = TRUE) +
   stat_poly_eq(method = "glm", method.args = list(family = poisson))

inst-not/quantreg/ggplo2-quantreg-rqss.R

@@ -0,0 +1,13 @@
+library(ggplot2)
+
+m <-
+  ggplot(mpg, aes(displ, 1 / hwy)) +
+  geom_point()
+m + stat_quantile()
+
+m + stat_quantile(method = "rqss")
+
+m + stat_quantile(method = "rqss", lambda = 0.1)
+
+sessionInfo()
+

inst-not/quantreg/ggpmisc-quantreg-rqss.R

@@ -0,0 +1,25 @@
+library(ggplot2)
+library(ggpmisc)
+
+p <-
+  ggplot(mpg, aes(displ, 1 / hwy)) +
+  geom_point()
+p + stat_quant_line()
+
+p + stat_quant_line(method = "rqss")
+
+p + stat_quant_line(method = "rqss", lambda = 0.1)
+
+p + stat_quant_band()
+
+p + stat_quant_band(method = "rqss")
+
+p + stat_quant_band(method = "rqss", lambda = 0.1)
+
+p + stat_quant_eq()
+
+p + stat_quant_eq(method = "rqss")
+
+p + stat_quant_eq(method = "rqss", lambda = 0.1)
+
+sessionInfo()

inst-not/quantreg/quantreg-rqss-examples.R

@@ -0,0 +1,29 @@
+library(quantreg)
+
+n <- 200
+x <- sort(rchisq(n,4))
+z <- x + rnorm(n)
+y <- log(x)+ .1*(log(x))^2 + log(x)*rnorm(n)/4 + z
+plot(x, y-z)
+
+f.N  <- rqss(y ~ qss(x, constraint= "N") + z)
+
+f.I  <- rqss(y ~ qss(x, constraint= "I") + z)
+
+f.CI <- rqss(y ~ qss(x, constraint= "CI") + z)
+
+lines(x[-1], f.N $coef[1] + f.N $coef[-(1:2)])
+
+lines(x[-1], f.I $coef[1] + f.I $coef[-(1:2)], col="blue")
+
+lines(x[-1], f.CI$coef[1] + f.CI$coef[-(1:2)], col="red")
+
+## A bivariate example
+if(requireNamespace("interp")){
+  if(requireNamespace("interp")){
+    data(CobarOre)
+    fCO <- rqss(z ~ qss(cbind(x,y), lambda= .08), data=CobarOre)
+    plot(fCO)
+  }}
+
+sessionInfo()