## ---- include = FALSE--------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.width = 7, fig.height = 4.8, fig.align = "center" ) ## ----setup, message=FALSE----------------------------------------------------- library(dplyr) library(ggplot2) library(qqboxplot) ## ----------------------------------------------------------------------------- simulated_data %>% ggplot(aes(factor(group, levels=c("normal, mean=2", "t distribution, df=32", "t distribution, df=16", "t distribution, df=8", "t distribution, df=4")), y=y)) + geom_qqboxplot(notch=TRUE, varwidth = TRUE, reference_dist="norm") + xlab("reference: normal distribution") + ylab(NULL) + guides(color=FALSE) + theme(axis.text.x = element_text(angle = 23, size = 15), axis.title.y = element_text(size=15), axis.title.x = element_text(size=15), panel.border = element_blank(), panel.background = element_rect(fill="white"), panel.grid = element_line(colour = "grey70")) ## ---- eval=FALSE-------------------------------------------------------------- # tibble(y=c(rnorm(1000, mean=2), rt(1000, 16), rt(500, 4), # rt(1000, 8), rt(1000, 32)), # group=c(rep("normal, mean=2", 1000), # rep("t distribution, df=16", 1000), # rep("t distribution, df=4", 500), # rep("t distribution, df=8", 1000), # rep("t distribution, df=32", 1000))) ## ----------------------------------------------------------------------------- simulated_data %>% ggplot(aes(factor(group, levels=c("normal, mean=2", "t distribution, df=32", "t distribution, df=16", "t distribution, df=8", "t distribution, df=4")), y=y)) + geom_qqboxplot(notch=TRUE, varwidth = TRUE, compdata=comparison_dataset) + xlab("reference: simulated normal dataset") + ylab(NULL) + theme(axis.text.x = element_text(angle = 23, size = 15), axis.title.y = element_text(size=15), axis.title.x = element_text(size=15), panel.border = element_blank(), panel.background = element_rect(fill="white"), panel.grid = element_line(colour = "grey70")) ## ---- eval=FALSE-------------------------------------------------------------- # rnorm(1000, 5)