Last updated: 2017-01-15
Code version: b05decc05714ddcb20aa04e56b557d5123d178fb
First, we load the necessary libraries.
library(ashr)
library(ggplot2)
library(dplyr)
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
Load the results of the simulation experiments, and generate the density data for all the simulation scenarios in a single data frame (“df”).
load("../output/dsc-shrink-files/res.RData")
PLOTSCENARIOS = c("spiky","near-normal","flat-top","skew","bimodal")
PLOTNAMES = PLOTSCENARIOS
df = data.frame()
for(i in PLOTSCENARIOS) {
s = dsc_shrink$scenarios[[i]]
g = s$args$g
x = seq(-6,6,length = 100)
y = as.numeric(dens(g,x))
df = rbind(df,data.frame(x = x,y = y,scenario = i))
}
df$scenario = factor(df$scenario,levels = PLOTSCENARIOS)
levels(df$scenario) = PLOTNAMES
Generate density plots using ggplot.
ggplot(df,aes(x = x,y = y)) +
geom_line(size = 1.2,linetype = 1) +
facet_grid(.~scenario) +
ylab("density")
sessionInfo()
R version 3.3.2 (2016-10-31)
Platform: x86_64-apple-darwin13.4.0 (64-bit)
Running under: macOS Sierra 10.12.2
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] knitr_1.15.1 dplyr_0.5.0 ggplot2_2.2.0 ashr_2.0.5
loaded via a namespace (and not attached):
[1] Rcpp_0.12.8 dscr_0.1.1 plyr_1.8.4
[4] iterators_1.0.8 tools_3.3.2 digest_0.6.10
[7] evaluate_0.10 tibble_1.2 gtable_0.2.0
[10] lattice_0.20-34 foreach_1.4.3 shiny_0.14.2
[13] DBI_0.5-1 yaml_2.1.14 parallel_3.3.2
[16] stringr_1.1.0 rprojroot_1.1 grid_3.3.2
[19] R6_2.2.0 rmarkdown_1.3 reshape2_1.4.2
[22] magrittr_1.5 backports_1.0.4 scales_0.4.1
[25] codetools_0.2-15 htmltools_0.3.5 MASS_7.3-45
[28] assertthat_0.1 xtable_1.8-2 mime_0.5
[31] colorspace_1.2-6 httpuv_1.3.3 labeling_0.3
[34] stringi_1.1.2 lazyeval_0.2.0 pscl_1.4.9
[37] doParallel_1.0.10 munsell_0.4.3 truncnorm_1.0-7
[40] SQUAREM_2016.8-2