The following code generate Tables 4,5 in the manuscript. 5 indepdent simulation are performed. All simulations RData files can be accessed at this online folder http://www.tonyjhwueng.info/ououcir/simulation64V3set3.
rm(list=ls())
library(knitr)
load(url("http://www.tonyjhwueng.info/ououcir/unifsimtable.RData"))
kable(bigoutputtable)| model | taxa | alpha.y | alpha.x | theta.x | sigmasq.x | tau | alpha.tau | theta.tau | sigmasq.tau | b0 | b1 | b2 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| oubmbm | 16 | 0.48 (0.05,0.96) | NA | NA | 2.45 (0.58,4.55) | 1.01 (0.11,1.91) | NA | NA | NA | 9.88 (5.52,14.49) | 3.3 (-0.6,8.17) | -2.51 (-7.23,1.53) |
| oubmbm | 32 | 0.47 (0.04,0.95) | NA | NA | 2.19 (0.65,4.52) | 1.01 (0.11,1.89) | NA | NA | NA | 9.9 (5.44,14.54) | 3.33 (-0.63,8.31) | -2.65 (-7.42,1.51) |
| oubmbm | 64 | 0.51 (0.06,0.95) | NA | NA | 2.36 (0.45,4.56) | 1.02 (0.1,1.9) | NA | NA | NA | 9.97 (5.42,14.46) | 3.68 (-0.42,8.31) | -2.81 (-7.4,1.49) |
| oubmbm | 128 | 0.5 (0.04,0.94) | NA | NA | 2.31 (0.65,4.44) | 0.98 (0.1,1.91) | NA | NA | NA | 10.04 (5.44,14.48) | 3.52 (-0.62,8.23) | -2.55 (-7.19,1.56) |
| ououbm | 16 | 0.52 (0.13,0.93) | 0.66 (0.07,1.4) | 0.03 (-2.68,2.69) | 2.46 (0.74,4.6) | 0.99 (0.09,1.88) | NA | NA | NA | 9.93 (5.57,14.49) | 4.41 (-0.17,8.45) | -2.94 (-7.31,1.46) |
| ououbm | 32 | 0.46 (0.07,0.93) | 0.82 (0.11,1.43) | -0.09 (-2.68,2.69) | 2.31 (0.59,4.49) | 0.98 (0.1,1.9) | NA | NA | NA | 9.91 (5.55,14.46) | 4.26 (-0.32,8.42) | -2.24 (-7.34,1.66) |
| ououbm | 64 | 0.48 (0.12,0.94) | 0.6 (0.07,1.39) | 0.01 (-2.72,2.69) | 2.38 (0.67,4.63) | 0.86 (0.08,1.86) | NA | NA | NA | 10.06 (5.55,14.52) | 4.31 (-0.38,8.53) | -2.58 (-7.3,1.57) |
| ououbm | 128 | 0.46 (0.08,0.91) | 0.74 (0.09,1.42) | 0.09 (-2.65,2.7) | 2.51 (0.85,4.45) | 0.98 (0.09,1.89) | NA | NA | NA | 9.92 (5.56,14.49) | 3.85 (-0.55,8.41) | -2.78 (-7.41,1.53) |
| oubmcir | 16 | 0.51 (0.05,0.95) | NA | NA | 2.15 (0.41,4.57) | NA | 0.66 (0.07,1.24) | 1.48 (0.14,2.85) | 0.97 (0.09,1.9) | 10.01 (5.48,14.46) | 3.62 (-0.53,8.37) | -2.71 (-7.37,1.52) |
| oubmcir | 32 | 0.53 (0.06,0.95) | NA | NA | 2.33 (0.6,4.54) | NA | 0.65 (0.06,1.24) | 1.48 (0.14,2.85) | 0.95 (0.1,1.89) | 10.1 (5.5,14.5) | 3.88 (-0.51,8.34) | -2.94 (-7.43,1.49) |
| oubmcir | 64 | 0.54 (0.07,0.96) | NA | NA | 2.49 (0.77,4.59) | NA | 0.66 (0.06,1.24) | 1.43 (0.14,2.84) | 0.88 (0.08,1.87) | 9.89 (5.47,14.51) | 3.89 (-0.47,8.34) | -3 (-7.36,1.51) |
| oubmcir | 128 | 0.56 (0.07,0.96) | NA | NA | 2.49 (0.82,4.52) | NA | 0.65 (0.06,1.24) | 1.4 (0.13,2.82) | 0.83 (0.08,1.85) | 9.99 (5.48,14.52) | 3.89 (-0.42,8.34) | -3.23 (-7.41,1.49) |
| ououcir | 16 | 0.55 (0.07,0.95) | 0.86 (0.11,1.44) | -0.04 (-2.7,2.67) | 2.31 (0.51,4.52) | NA | 0.62 (0.07,1.23) | 1.45 (0.16,2.84) | 0.97 (0.11,1.88) | 10.06 (5.45,14.41) | 3.78 (-0.54,8.55) | -3.15 (-7.49,1.52) |
| ououcir | 32 | 0.57 (0.08,0.95) | 0.75 (0.08,1.43) | -0.07 (-2.7,2.66) | 2.63 (0.74,4.59) | NA | 0.66 (0.05,1.25) | 1.61 (0.21,2.9) | 0.93 (0.1,1.89) | 10.05 (5.49,14.53) | 4.38 (-0.47,8.49) | -2.9 (-7.53,1.42) |
| ououcir | 64 | 0.58 (0.09,0.96) | 0.95 (0.16,1.45) | 0.18 (-2.63,2.69) | 2.71 (0.95,4.58) | NA | 0.62 (0.06,1.23) | 1.59 (0.18,2.84) | 0.87 (0.09,1.86) | 10.05 (5.46,14.56) | 3.88 (-0.5,8.5) | -3.16 (-7.51,1.51) |
| ououcir | 128 | 0.47 (0.05,0.94) | 0.84 (0.11,1.42) | 0.04 (-2.68,2.63) | 2.34 (0.74,4.44) | NA | 0.63 (0.07,1.23) | 1.5 (0.22,2.83) | 1.08 (0.25,1.91) | 9.94 (5.48,14.47) | 3.69 (-0.58,8.48) | -2.8 (-7.37,1.52) |
The following is raw code by loading RData across 5 sims.
### BIG TABLE FOR ALL PARAMETERS IN MODELS
rm(list=ls())
library(xtable)
simfolder<-"http://www.tonyjhwueng.info/ououcir/simulation64V3set3/"
simsets<-paste("uniformset",1:5,sep="")
foldername<-c("oubmbm","ououbm","oubmcir","ououcir")
n.array<-c(16,32,64,128)
bigoutputtable<- array(NA,c(16,13))
colnames(bigoutputtable)<-c("model","taxa","alpha.y","alpha.x","theta.x","sigmasq.x","tau","alpha.tau","theta.tau","sigmasq.tau","b0","b1","b2")
bigoutputtable[,1]<-rep(c("oubmbm","ououbm","oubmcir","ououcir") ,each=4)
bigoutputtable[,2]<-rep(c(16,32,64,128) ,times=4)
count<-0
for(folderIndex in 1: length(foldername)){
# folderIndex<-1
for(sizeIndex in 1:length(n.array)){
# sizeIndex<-1
count<-count+1
postsample<-NULL
for(simsetIndex in 1:length(simsets)){
# simsetIndex<-1
folder<-paste(simfolder,simsets[simsetIndex],"/",foldername[folderIndex],sep = "")
# folder
setwd(folder)
rfile<-paste(foldername[folderIndex],"SimV2size",n.array[sizeIndex],".RData",sep="")
try(load(rfile))
postsample<-rbind(postsample,get(paste("post.",foldername[folderIndex],sep="")))
}
meanpost<-round(apply(postsample,2, median),2)
qrpost<-round(apply(postsample,2,quantile,probs=c(0.05,0.95)),2)
meanqrpost<-paste(meanpost," (",qrpost[1,],",",qrpost[2,],")",sep="")
names(meanqrpost)<-names(meanpost)
fillposition<-colnames(bigoutputtable)%in%names(meanpost)
bigoutputtable[count,fillposition]<-meanqrpost
}
}
print(bigoutputtable)
xtable(bigoutputtable[,1:10])
xtable(bigoutputtable[,c(1,2,11:13)])
#save(bigoutputtable,file="unifsimtable.RData")