## ----warning=F, message=F----------------------------------------------------- library("IHWpaper") library("fdrtool") library("ggplot2") library("cowplot") theme_set(theme_cowplot()) ## ----------------------------------------------------------------------------- sim <- du_ttest_sim(100, 0.5, 2.5 ,seed=100) sorted_pvalues <- sort(sim$pvalue) n <- length(sorted_pvalues) unique_pvalues <- unique(sorted_pvalues) ecdf_values <- cumsum(tabulate(match(sorted_pvalues, unique_pvalues)))/n df_ecdf <- data.frame(x=unique_pvalues,y=ecdf_values) gren <- IHW:::presorted_grenander(sorted_pvalues) df_gren <- data.frame(x=gren$x.knots, y=gren$y.knots) ## ----------------------------------------------------------------------------- ggplot(df_ecdf, aes(x=x, y=y)) + geom_step(direction="hv",size=1.3) + scale_x_continuous(expand=c(0,0),lim=c(0,1))+ scale_y_continuous(expand=c(0,0))+ xlab("p-value") + ylab("Distribution") ## ----eval=FALSE--------------------------------------------------------------- # ggsave(filename="ecdf_plot.pdf", width=7,height=7) ## ----------------------------------------------------------------------------- ggplot(df_ecdf, aes(x=x, y=y)) + geom_step(direction="hv",size=1.3) + geom_line(data=df_gren, aes(x=x,y=y), color="red",size=1.3) + scale_x_continuous(expand=c(0,0),lim=c(0,1))+ scale_y_continuous(expand=c(0,0))+ xlab("p-value") + ylab("Distribution") ## ----eval=FALSE--------------------------------------------------------------- # ggsave(filename="ecdf_grenander_plot.pdf", width=7,height=7)