CIS_paper/Figures.R
In markusloecher/rfVarImpOOB: Unbiased Variable Importance for Random Forests
library("latex2exp")
library(rfVarImpOOB)
library(ggplot2)
baseDir = "./"
setwd("~/research/randomforest_investigation/JournalPaper/CIS")
source(paste0(baseDir, "SimulateData.R"))
Figs1_2=FALSE
Figs3_4=FALSE
Figs5_6=TRUE
if (Figs1_2){
naRows = is.na(titanic_train$Age)
data2=titanic_train[!naRows,]
rf3 =randomForest(Survived ~ Age + Sex + Pclass + PassengerId, data=data2, ntree=100,importance=TRUE,mtry=2, keep.inbag=TRUE)
if (is.factor(data2$Survived)) data2$Survived = as.numeric(data2$Survived)-1
VI_PMDI21 = GiniImportanceForest(rf3, data2,score="PMDI21",Predictor=mean)
plots21 = plotVI2(VI_PMDI21, score="PMDI1", decreasing = TRUE,nrow=1)
pl1 = ggpubr::ggarrange(plots21$inbag_plot, plots21$MDA_plot, widths = 40, heights = 40,nrow=1,ncol=2)
pdf(paste0(baseDir, "figures/TitanicVarImp1.pdf"), height=1.5, width=5)
par(cex=1.25)
print(pl1)
dev.off()
VI_PMDI20 = GiniImportanceForest(rf3, data2,score="PMDI00",Predictor=mean)
VI_PMDI22 = GiniImportanceForest(rf3, data2,score="PMDI22",Predictor=mean)
VI_PMDI23 = GiniImportanceForest(rf3, data2,score="PMDI23",Predictor=mean)
plots20 = plotVI2(VI_PMDI20, score="PMDI0", decreasing = TRUE,nrow=1)
plots22 = plotVI2(VI_PMDI22, score="PMDI2", decreasing = TRUE,nrow=1)
plots23 = plotVI2(VI_PMDI23, score="PMDI3", decreasing = TRUE,nrow=1)
pl2 = ggpubr::ggarrange(plots20$OOB_plot+ ggtitle(TeX("PG_{OOB}^{(0)}")),
plots21$OOB_plot+ ggtitle(TeX("PG_{OOB}^{(1)}")),
plots22$OOB_plot+ ggtitle(TeX("PG_{OOB}^{(2)}")),
plots23$OOB_plot+ ggtitle(TeX("PG_{OOB}^{(3)}")),
widths = 40, heights = 40,nrow=1,ncol=4)
pdf(paste0(baseDir, "figures/TitanicVarImpOOB.pdf") , height=2, width=8)
par(cex=1.25)
print(pl2)
dev.off()
save(VI_PMDI20,VI_PMDI21,VI_PMDI22,VI_PMDI23, file = "Figs2-3.rda")
#plots21$OOB_plot
}
###########################################################
if (Figs3_4){
set.seed(123)
load("../data/arabidopsis.rda")
arabidopsis$sfe = sample(arabidopsis$fe)#shuffle fe as a random feature
RF2 <- randomForest(edit ~ ., data = arabidopsis, keep.inbag=TRUE,
importance = TRUE, ntree = 50, mtry = 3)
rfobj <- ranger(edit ~ ., data = arabidopsis, keep.inbag=TRUE, importance = "impurity_corrected",
num.trees =50, mtry = 3)
VI_AIR = rfobj$variable.importance # Nembrinin et al, Actual impurity reduction importance
AIR_df = cbind.data.frame(Value=VI_AIR, Variable=factor(VI_PMDI21$Variable,levels=VI_PMDI21$Variable))
plots4 = ggplot2::ggplot(AIR_df)+
geom_bar(aes_string(x="Variable", y="Value", fill = "Variable"), stat='identity')+ # coord_flip() +
theme(legend.position="none",axis.title.x=element_blank(),axis.title.y=element_blank(),text = element_text(size=10)) +
guides(fill=guide_legend(title="Variables:")) +
ggtitle(paste0("AIR"))
if (is.factor(arabidopsis$edit)) {
print("converting factor to binary 0/1 label for GiniImportanceForest")
arabidopsis$edit = as.numeric(arabidopsis$edit)-1
}
#look up font size axis labels ggplot and horizontal bar plots
VI_PMDI21 = GiniImportanceForest(RF2, arabidopsis,score="PMDI21",Predictor=mean, ylabel="edit")
VI_PMDI22 = GiniImportanceForest(RF2, arabidopsis,score="PMDI22",Predictor=mean, ylabel="edit")
VI_PMDI23 = GiniImportanceForest(RF2, arabidopsis,score="PMDI23",Predictor=mean, ylabel="edit")
rownames(VI_PMDI21)= gsub("X.", "-", rownames(VI_PMDI21), fixed = TRUE);rownames(VI_PMDI21)= gsub("X", "", rownames(VI_PMDI21), fixed = TRUE)
rownames(VI_PMDI22)= gsub("X.", "-", rownames(VI_PMDI22), fixed = TRUE);rownames(VI_PMDI22)= gsub("X", "", rownames(VI_PMDI22), fixed = TRUE)
rownames(VI_PMDI23)= gsub("X.", "-", rownames(VI_PMDI23), fixed = TRUE);rownames(VI_PMDI23)= gsub("X", "", rownames(VI_PMDI23), fixed = TRUE)
plots21 = plotVI2(VI_PMDI21, score="PMDI1", decreasing = TRUE,nrow=1,ordered_by="orig",horizontal = FALSE)
plots22 = plotVI2(VI_PMDI22, score="PMDI2", decreasing = TRUE,nrow=1,ordered_by="orig",horizontal = FALSE)
plots23 = plotVI2(VI_PMDI23, score="PMDI3", decreasing = TRUE,nrow=1,ordered_by="orig",horizontal = FALSE)
pl3a = ggpubr::ggarrange(plots21$inbag_plot, plots21$MDA_plot, widths = 40, heights = 40,nrow=2,ncol=2)
pdf(paste0(baseDir, "figures/arabidopsisVarImp1.pdf"), height=2.5, width=8)
par(cex=1)
print(pl3a)
dev.off()
pl3b = ggpubr::ggarrange(plots21$OOB_plot+ ggtitle(TeX("PG_{OOB}^{(1)}")), plots22$OOB_plot+ ggtitle(TeX("PG_{OOB}^{(2)}")),plots23$OOB_plot+ ggtitle(TeX("PG_{OOB}^{(3)}")), plots4, widths = 40, heights = 40,nrow=4,ncol=1)
pdf(paste0(baseDir, "figures/arabidopsisVarImpOOB.pdf"), height=8, width=8)
par(cex=1)
print(pl3b)
dev.off()
pl3b2x2 = ggpubr::ggarrange(plots21$OOB_plot+ ggtitle(TeX("PG_{OOB}^{(1)}")), plots22$OOB_plot+ ggtitle(TeX("PG_{OOB}^{(2)}")),plots23$OOB_plot+ ggtitle(TeX("PG_{OOB}^{(3)}")), plots4, widths = 40, heights = 40,nrow=2,ncol=2)
pdf(paste0(baseDir, "figures/arabidopsisVarImpOOB_2x2.pdf"), height=5, width=8)
par(cex=1)
print(pl3b2x2)
dev.off()
VI_PMDI21$Variable = rownames(VI_PMDI21)
MDA = VI_PMDI21[,c('Variable', 'MeanDecreaseAccuracy')]
MDA$Variable = factor(MDA$Variable)
MDA_plot = ggplot(MDA)+
geom_bar(aes_string(x="Variable", y="MeanDecreaseAccuracy",fill="Variable"), fill="blue", stat='identity')+ NULL+
#coord_flip() +
theme(legend.position="none",axis.title.x=element_blank(),axis.title.y=element_blank()) +
guides(fill=guide_legend(title="Variables:")) +
ggtitle("MDA") + theme(text = element_text(size=5))
MDA_plot
}
##Simulation data
if (Figs5_6){
#NullSim=list(OOB_sim_1=OOB_sim_1,OOB_sim_2=OOB_sim_2,MDI_sim=MDI_sim)
NullSim=SimulateData(relevance = 0)#, verbose=1, M=2, ntree = 5)
NullSim03 =SimulateData03(relevance = 0)#, verbose=1, M=2, ntree = 5)
NullSimTI =SimulateDataTI(relevance = 0)
#boxplot(t(NullSimTI),main="tree.interpreter",ylab="");grid();abline(h=0,col=2,lty=2)
#################################NullSim.pdf, Fig5
fname=paste0(baseDir, "figures/NullSim_",Sys.Date(),".pdf")
pdf(fname, height=6, width=8)
par(mfrow=c(2,3),cex=0.85, mar=c(3,3,4,1))
boxplot(t(NullSim$MDI_sim),main=TeX("MDI"),ylab="");grid();abline(h=0,col=2,lty=2)
mtext("Importance", side = 2,line=2)
boxplot(t(NullSim03$MDI_sim),main=TeX("AIR"),ylab="");grid();abline(h=0,col=2,lty=2)
boxplot(t(NullSim03$OOB_sim_0),main=TeX("PG_{OOB}^{(0)}"),ylab="", ylim = c(-1,2));grid();abline(h=0,col=2,lty=2)
boxplot(t(NullSim$OOB_sim_1)/4,main=TeX("PG_{OOB}^{(1)}"),ylab="", ylim = c(-1,2));grid();abline(h=0,col=2,lty=2)
boxplot(t(NullSim$OOB_sim_2),main=TeX("PG_{OOB}^{(2)}"),ylab="", ylim = c(-1,2));grid();abline(h=0,col=2,lty=2)
boxplot(t(NullSim03$OOB_sim_3)/2,main=TeX("PG_{OOB}^{(3)}"),ylab="", ylim = c(-1,2));grid();abline(h=0,col=2,lty=2)
dev.off()
par(mfrow=c(1,3),cex=0.85, mar=c(3,3,4,1))
boxplot(t(NullSim03$MDI_sim),main=TeX("MDI"),ylab="");grid()
mtext("Importance", side = 2,line=2)
boxplot(t(NullSim03$OOB_sim_0),main=TeX("PG_{OOB}^{(0)}"),ylab="");grid()
boxplot(t(NullSim03$OOB_sim_3),main=TeX("PG_{OOB}^{(3)}"),ylab="");grid()
#################################PowerSim.pdf, Fig6
PowerSim=PowerSim03=NULL
PowerSim=SimulateData(relevance = 0.15)
PowerSim03=SimulateData03(relevance = 0.15)
PowerSimTI =SimulateDataTI(relevance = 0.15)
boxplot(t(PowerSimTI),main="tree.interpreter",ylab="");grid();abline(h=0,col=2,lty=2)
fname=paste0(baseDir, "figures/PowerSim_",Sys.Date(),".pdf")
plotImp(PowerSim,PowerSim03,fname)
#PowerSim=SimulateData(M=20,relevance = 0.15, prevResults=PowerSim)
#PowerSim03=SimulateData03(M=20,relevance = 0.15, prevResults=PowerSim03)
pdf(fname, height=3, width=8)
par(mfrow=c(1,3),cex=0.85, mar=c(3,3,4,1))
boxplot(PowerSim$MDI_sim,main=TeX("MDI"),ylab="");grid();
mtext("Importance", side = 2,line=2)
boxplot(PowerSim$OOB_sim_1,main=TeX("PG_{OOB}^{(1)}"),ylab="", ylim = c(-4,2));grid()
boxplot(PowerSim$OOB_sim_2,main=TeX("PG_{OOB}^{(2)}"),ylab="", ylim = c(-4,2));grid()
dev.off()
#VI_sim_22 = GiniImportanceForest(RF3, data,score="PMDI22",Predictor=mean, ylabel="y")
#VI_sim_23 = GiniImportanceForest(RF3, data,score="PMDI23",Predictor=mean, ylabel="y")
}
if (Fig8){
load("OOB_mod_sims.rda")
fname=paste0(baseDir, "figures/OOBhat_PowerNullSim_",Sys.Date(),".pdf")
pdf(fname, height=3, width=8)
par(mfrow=c(1,2),cex=1, mar=c(3,3,4,1))
boxplot(t(NullSim03$OOB_sim_0),main="Null",ylab="", ylim = c(-1,1));grid();abline(h=0,col=2,lty=2)
mtext(TeX("\\widehat{PG}_{OOB}^{(0)}"), side = 3,line=-1.75,outer=TRUE)
boxplot(t(PowerSim03$OOB_sim_0),main="Power",ylab="", ylim = c(-1,2));grid();abline(h=0,col=2,lty=2)
dev.off()
}
l=paste0(c("12","34","56")[c(Figs1_2,Figs3_4,Figs5_6)],collapse="_")
#save.image(paste0("Figures",l,".rda"))
save.image(paste0("Figures",l,"_",Sys.Date(),".rda"))
markusloecher/rfVarImpOOB documentation built on July 5, 2020, 6:50 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
library("latex2exp")
library(rfVarImpOOB)
library(ggplot2)
baseDir = "./"
setwd("~/research/randomforest_investigation/JournalPaper/CIS")
source(paste0(baseDir, "SimulateData.R"))
Figs1_2=FALSE
Figs3_4=FALSE
Figs5_6=TRUE
if (Figs1_2){
naRows = is.na(titanic_train$Age)
data2=titanic_train[!naRows,]
rf3 =randomForest(Survived ~ Age + Sex + Pclass + PassengerId, data=data2, ntree=100,importance=TRUE,mtry=2, keep.inbag=TRUE)
if (is.factor(data2$Survived)) data2$Survived = as.numeric(data2$Survived)-1
VI_PMDI21 = GiniImportanceForest(rf3, data2,score="PMDI21",Predictor=mean)
plots21 = plotVI2(VI_PMDI21, score="PMDI1", decreasing = TRUE,nrow=1)
pl1 = ggpubr::ggarrange(plots21$inbag_plot, plots21$MDA_plot, widths = 40, heights = 40,nrow=1,ncol=2)
pdf(paste0(baseDir, "figures/TitanicVarImp1.pdf"), height=1.5, width=5)
par(cex=1.25)
print(pl1)
dev.off()
VI_PMDI20 = GiniImportanceForest(rf3, data2,score="PMDI00",Predictor=mean)
VI_PMDI22 = GiniImportanceForest(rf3, data2,score="PMDI22",Predictor=mean)
VI_PMDI23 = GiniImportanceForest(rf3, data2,score="PMDI23",Predictor=mean)
plots20 = plotVI2(VI_PMDI20, score="PMDI0", decreasing = TRUE,nrow=1)
plots22 = plotVI2(VI_PMDI22, score="PMDI2", decreasing = TRUE,nrow=1)
plots23 = plotVI2(VI_PMDI23, score="PMDI3", decreasing = TRUE,nrow=1)
pl2 = ggpubr::ggarrange(plots20$OOB_plot+ ggtitle(TeX("PG_{OOB}^{(0)}")),
plots21$OOB_plot+ ggtitle(TeX("PG_{OOB}^{(1)}")),
plots22$OOB_plot+ ggtitle(TeX("PG_{OOB}^{(2)}")),
plots23$OOB_plot+ ggtitle(TeX("PG_{OOB}^{(3)}")),
widths = 40, heights = 40,nrow=1,ncol=4)
pdf(paste0(baseDir, "figures/TitanicVarImpOOB.pdf") , height=2, width=8)
par(cex=1.25)
print(pl2)
dev.off()
save(VI_PMDI20,VI_PMDI21,VI_PMDI22,VI_PMDI23, file = "Figs2-3.rda")
#plots21$OOB_plot
}
###########################################################
if (Figs3_4){
set.seed(123)
load("../data/arabidopsis.rda")
arabidopsis$sfe = sample(arabidopsis$fe)#shuffle fe as a random feature
RF2 <- randomForest(edit ~ ., data = arabidopsis, keep.inbag=TRUE,
importance = TRUE, ntree = 50, mtry = 3)
rfobj <- ranger(edit ~ ., data = arabidopsis, keep.inbag=TRUE, importance = "impurity_corrected",
num.trees =50, mtry = 3)
VI_AIR = rfobj$variable.importance # Nembrinin et al, Actual impurity reduction importance
AIR_df = cbind.data.frame(Value=VI_AIR, Variable=factor(VI_PMDI21$Variable,levels=VI_PMDI21$Variable))
plots4 = ggplot2::ggplot(AIR_df)+
geom_bar(aes_string(x="Variable", y="Value", fill = "Variable"), stat='identity')+ # coord_flip() +
theme(legend.position="none",axis.title.x=element_blank(),axis.title.y=element_blank(),text = element_text(size=10)) +
guides(fill=guide_legend(title="Variables:")) +
ggtitle(paste0("AIR"))
if (is.factor(arabidopsis$edit)) {
print("converting factor to binary 0/1 label for GiniImportanceForest")
arabidopsis$edit = as.numeric(arabidopsis$edit)-1
}
#look up font size axis labels ggplot and horizontal bar plots
VI_PMDI21 = GiniImportanceForest(RF2, arabidopsis,score="PMDI21",Predictor=mean, ylabel="edit")
VI_PMDI22 = GiniImportanceForest(RF2, arabidopsis,score="PMDI22",Predictor=mean, ylabel="edit")
VI_PMDI23 = GiniImportanceForest(RF2, arabidopsis,score="PMDI23",Predictor=mean, ylabel="edit")
rownames(VI_PMDI21)= gsub("X.", "-", rownames(VI_PMDI21), fixed = TRUE);rownames(VI_PMDI21)= gsub("X", "", rownames(VI_PMDI21), fixed = TRUE)
rownames(VI_PMDI22)= gsub("X.", "-", rownames(VI_PMDI22), fixed = TRUE);rownames(VI_PMDI22)= gsub("X", "", rownames(VI_PMDI22), fixed = TRUE)
rownames(VI_PMDI23)= gsub("X.", "-", rownames(VI_PMDI23), fixed = TRUE);rownames(VI_PMDI23)= gsub("X", "", rownames(VI_PMDI23), fixed = TRUE)
plots21 = plotVI2(VI_PMDI21, score="PMDI1", decreasing = TRUE,nrow=1,ordered_by="orig",horizontal = FALSE)
plots22 = plotVI2(VI_PMDI22, score="PMDI2", decreasing = TRUE,nrow=1,ordered_by="orig",horizontal = FALSE)
plots23 = plotVI2(VI_PMDI23, score="PMDI3", decreasing = TRUE,nrow=1,ordered_by="orig",horizontal = FALSE)
pl3a = ggpubr::ggarrange(plots21$inbag_plot, plots21$MDA_plot, widths = 40, heights = 40,nrow=2,ncol=2)
pdf(paste0(baseDir, "figures/arabidopsisVarImp1.pdf"), height=2.5, width=8)
par(cex=1)
print(pl3a)
dev.off()
pl3b = ggpubr::ggarrange(plots21$OOB_plot+ ggtitle(TeX("PG_{OOB}^{(1)}")), plots22$OOB_plot+ ggtitle(TeX("PG_{OOB}^{(2)}")),plots23$OOB_plot+ ggtitle(TeX("PG_{OOB}^{(3)}")), plots4, widths = 40, heights = 40,nrow=4,ncol=1)
pdf(paste0(baseDir, "figures/arabidopsisVarImpOOB.pdf"), height=8, width=8)
par(cex=1)
print(pl3b)
dev.off()
pl3b2x2 = ggpubr::ggarrange(plots21$OOB_plot+ ggtitle(TeX("PG_{OOB}^{(1)}")), plots22$OOB_plot+ ggtitle(TeX("PG_{OOB}^{(2)}")),plots23$OOB_plot+ ggtitle(TeX("PG_{OOB}^{(3)}")), plots4, widths = 40, heights = 40,nrow=2,ncol=2)
pdf(paste0(baseDir, "figures/arabidopsisVarImpOOB_2x2.pdf"), height=5, width=8)
par(cex=1)
print(pl3b2x2)
dev.off()
VI_PMDI21$Variable = rownames(VI_PMDI21)
MDA = VI_PMDI21[,c('Variable', 'MeanDecreaseAccuracy')]
MDA$Variable = factor(MDA$Variable)
MDA_plot = ggplot(MDA)+
geom_bar(aes_string(x="Variable", y="MeanDecreaseAccuracy",fill="Variable"), fill="blue", stat='identity')+ NULL+
#coord_flip() +
theme(legend.position="none",axis.title.x=element_blank(),axis.title.y=element_blank()) +
guides(fill=guide_legend(title="Variables:")) +
ggtitle("MDA") + theme(text = element_text(size=5))
MDA_plot
}
##Simulation data
if (Figs5_6){
#NullSim=list(OOB_sim_1=OOB_sim_1,OOB_sim_2=OOB_sim_2,MDI_sim=MDI_sim)
NullSim=SimulateData(relevance = 0)#, verbose=1, M=2, ntree = 5)
NullSim03 =SimulateData03(relevance = 0)#, verbose=1, M=2, ntree = 5)
NullSimTI =SimulateDataTI(relevance = 0)
#boxplot(t(NullSimTI),main="tree.interpreter",ylab="");grid();abline(h=0,col=2,lty=2)
#################################NullSim.pdf, Fig5
fname=paste0(baseDir, "figures/NullSim_",Sys.Date(),".pdf")
pdf(fname, height=6, width=8)
par(mfrow=c(2,3),cex=0.85, mar=c(3,3,4,1))
boxplot(t(NullSim$MDI_sim),main=TeX("MDI"),ylab="");grid();abline(h=0,col=2,lty=2)
mtext("Importance", side = 2,line=2)
boxplot(t(NullSim03$MDI_sim),main=TeX("AIR"),ylab="");grid();abline(h=0,col=2,lty=2)
boxplot(t(NullSim03$OOB_sim_0),main=TeX("PG_{OOB}^{(0)}"),ylab="", ylim = c(-1,2));grid();abline(h=0,col=2,lty=2)
boxplot(t(NullSim$OOB_sim_1)/4,main=TeX("PG_{OOB}^{(1)}"),ylab="", ylim = c(-1,2));grid();abline(h=0,col=2,lty=2)
boxplot(t(NullSim$OOB_sim_2),main=TeX("PG_{OOB}^{(2)}"),ylab="", ylim = c(-1,2));grid();abline(h=0,col=2,lty=2)
boxplot(t(NullSim03$OOB_sim_3)/2,main=TeX("PG_{OOB}^{(3)}"),ylab="", ylim = c(-1,2));grid();abline(h=0,col=2,lty=2)
dev.off()
par(mfrow=c(1,3),cex=0.85, mar=c(3,3,4,1))
boxplot(t(NullSim03$MDI_sim),main=TeX("MDI"),ylab="");grid()
mtext("Importance", side = 2,line=2)
boxplot(t(NullSim03$OOB_sim_0),main=TeX("PG_{OOB}^{(0)}"),ylab="");grid()
boxplot(t(NullSim03$OOB_sim_3),main=TeX("PG_{OOB}^{(3)}"),ylab="");grid()
#################################PowerSim.pdf, Fig6
PowerSim=PowerSim03=NULL
PowerSim=SimulateData(relevance = 0.15)
PowerSim03=SimulateData03(relevance = 0.15)
PowerSimTI =SimulateDataTI(relevance = 0.15)
boxplot(t(PowerSimTI),main="tree.interpreter",ylab="");grid();abline(h=0,col=2,lty=2)
fname=paste0(baseDir, "figures/PowerSim_",Sys.Date(),".pdf")
plotImp(PowerSim,PowerSim03,fname)
#PowerSim=SimulateData(M=20,relevance = 0.15, prevResults=PowerSim)
#PowerSim03=SimulateData03(M=20,relevance = 0.15, prevResults=PowerSim03)
pdf(fname, height=3, width=8)
par(mfrow=c(1,3),cex=0.85, mar=c(3,3,4,1))
boxplot(PowerSim$MDI_sim,main=TeX("MDI"),ylab="");grid();
mtext("Importance", side = 2,line=2)
boxplot(PowerSim$OOB_sim_1,main=TeX("PG_{OOB}^{(1)}"),ylab="", ylim = c(-4,2));grid()
boxplot(PowerSim$OOB_sim_2,main=TeX("PG_{OOB}^{(2)}"),ylab="", ylim = c(-4,2));grid()
dev.off()
#VI_sim_22 = GiniImportanceForest(RF3, data,score="PMDI22",Predictor=mean, ylabel="y")
#VI_sim_23 = GiniImportanceForest(RF3, data,score="PMDI23",Predictor=mean, ylabel="y")
}
if (Fig8){
load("OOB_mod_sims.rda")
fname=paste0(baseDir, "figures/OOBhat_PowerNullSim_",Sys.Date(),".pdf")
pdf(fname, height=3, width=8)
par(mfrow=c(1,2),cex=1, mar=c(3,3,4,1))
boxplot(t(NullSim03$OOB_sim_0),main="Null",ylab="", ylim = c(-1,1));grid();abline(h=0,col=2,lty=2)
mtext(TeX("\\widehat{PG}_{OOB}^{(0)}"), side = 3,line=-1.75,outer=TRUE)
boxplot(t(PowerSim03$OOB_sim_0),main="Power",ylab="", ylim = c(-1,2));grid();abline(h=0,col=2,lty=2)
dev.off()
}
l=paste0(c("12","34","56")[c(Figs1_2,Figs3_4,Figs5_6)],collapse="_")
#save.image(paste0("Figures",l,".rda"))
save.image(paste0("Figures",l,"_",Sys.Date(),".rda"))
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.