R version 3.2.2 (2015-08-14) -- "Fire Safety" Copyright (C) 2015 The R Foundation for Statistical Computing Platform: x86_64-pc-linux-gnu (64-bit) R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > x <- c(83.36,83.61,83.41,83.64,84.06,83.93,84.1,84.37,84.18,84.11,84.56,84.2,84.45,84.28,84.28,84.7,85.04,85.31,85.18,85.02,86.31,86.56,86.4,86.84,87.42,87.28,87.27,87.73,87.32,87.15,87.5,87.43,88.81,89.38,88.83,88.91,89.34,89.56,89.32,89.31,89.45,88.92,89.35,88.89,90.1,90.49,89.96,89.93,90.32,90.24,90.61,91.06,90.81,91.09,91.17,90.87,91.92,92.67,92.03,92.09,92.61,92.19,92.68,92.66,92.77,92.21,92.58,91.9,93.81,94.05,94.51,94.49,94.36,94.72,95.57,95.87,95.93,96.09,95.82,96.06,97.09,97.67,98.53,98.12,98.84,98.98,100.04,99.47,99.84,99.52,99.81,99.55,100.21,101.44,101,101.32,101.84,101.81,101.83,102.18,101.97,101.8,101.69,101.91,102.27,102.73,102.61,102.89) > par4 = 'P1 P5 Q1 Q3 P95 P99' > par3 = '0' > par2 = '5' > par1 = '750' > par4 <- 'P1 P5 Q1 Q3 P95 P99' > par3 <- '0' > par2 <- '5' > par1 <- '750' > #'GNU S' R Code compiled by R2WASP v. 1.2.327 (Wed, 25 Nov 2015 11:13:57 +0000) > #Author: root > #To cite this work: Wessa P., (2015), Bootstrap Plot for Central Tendency (v1.0.14) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_bootstrapplot1.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > # > par1 <- as.numeric(par1) > par2 <- as.numeric(par2) > if (par3 == '0') bw <- NULL > if (par3 != '0') bw <- as.numeric(par3) > if (par1 < 10) par1 = 10 > if (par1 > 5000) par1 = 5000 > library(modeest) This is package 'modeest' written by P. PONCET. For a complete list of functions, use 'library(help = "modeest")' or 'help.start()'. > library(lattice) > library(boot) Attaching package: 'boot' The following object is masked from 'package:lattice': melanoma > boot.stat <- function(s,i) + { + s.mean <- mean(s[i]) + s.median <- median(s[i]) + s.midrange <- (max(s[i]) + min(s[i])) / 2 + s.mode <- mlv(s[i], method='mfv')$M + s.kernelmode <- mlv(s[i], method='kernel', bw=bw)$M + c(s.mean, s.median, s.midrange, s.mode, s.kernelmode) + } > x<-na.omit(x) > (r <- boot(x,boot.stat, R=par1, stype='i')) ORDINARY NONPARAMETRIC BOOTSTRAP Call: boot(data = x, statistic = boot.stat, R = par1, stype = "i") Bootstrap Statistics : original bias std. error t1* 92.16917 0.00459716 0.58498213 t2* 91.07500 0.13464000 0.80609565 t3* 93.12500 -0.02100000 0.09839873 t4* 84.28000 7.11000559 5.11400923 t5* 90.03481 -0.87659205 2.39946769 Warning message: In .deal.ties(ny, i, tie.action, tie.limit) : encountered a tie, and the difference between minimal and maximal value is > length('x') * 'tie.limit' the distribution could be multimodal > postscript(file="/var/wessaorg/rcomp/tmp/1cidc1448965915.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(r$t[,1],type='p',ylab='simulated values',main='Simulation of Mean') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/254v51448965915.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(r$t[,2],type='p',ylab='simulated values',main='Simulation of Median') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/3dk2k1448965915.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(r$t[,3],type='p',ylab='simulated values',main='Simulation of Midrange') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/4g8u51448965915.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(r$t[,4],type='p',ylab='simulated values',main='Simulation of Mode') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/53zd01448965915.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(r$t[,5],type='p',ylab='simulated values',main='Simulation of Mode of Kernel Density') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/68gj41448965915.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~r$t[,1],col='black',main='Density Plot',xlab='mean') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/79yzh1448965915.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~r$t[,2],col='black',main='Density Plot',xlab='median') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/8lggg1448965915.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~r$t[,3],col='black',main='Density Plot',xlab='midrange') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/9q93y1448965915.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~r$t[,4],col='black',main='Density Plot',xlab='mode') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/10wbgf1448965915.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~r$t[,5],col='black',main='Density Plot',xlab='mode of kernel dens.') > dev.off() null device 1 > z <- data.frame(cbind(r$t[,1],r$t[,2],r$t[,3],r$t[,4],r$t[,5])) > colnames(z) <- list('mean','median','midrange','mode','mode k.dens') > postscript(file="/var/wessaorg/rcomp/tmp/11zlox1448965915.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > boxplot(z,notch=TRUE,ylab='simulated values',main='Bootstrap Simulation - Central Tendency') Warning message: In bxp(list(stats = c(90.675462962963, 91.7675, 92.1863425925926, : some notches went outside hinges ('box'): maybe set notch=FALSE > grid() > dev.off() null device 1 > > #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'Estimation Results of Bootstrap',10,TRUE) > a<-table.row.end(a) > if (par4 == 'P1 P5 Q1 Q3 P95 P99') { + myq.1 <- 0.01 + myq.2 <- 0.05 + myq.3 <- 0.95 + myq.4 <- 0.99 + myl.1 <- 'P1' + myl.2 <- 'P5' + myl.3 <- 'P95' + myl.4 <- 'P99' + } > if (par4 == 'P0.5 P2.5 Q1 Q3 P97.5 P99.5') { + myq.1 <- 0.005 + myq.2 <- 0.025 + myq.3 <- 0.975 + myq.4 <- 0.995 + myl.1 <- 'P0.5' + myl.2 <- 'P2.5' + myl.3 <- 'P97.5' + myl.4 <- 'P99.5' + } > if (par4 == 'P10 P20 Q1 Q3 P80 P90') { + myq.1 <- 0.10 + myq.2 <- 0.20 + myq.3 <- 0.80 + myq.4 <- 0.90 + myl.1 <- 'P10' + myl.2 <- 'P20' + myl.3 <- 'P80' + myl.4 <- 'P90' + } > a<-table.row.start(a) > a<-table.element(a,'statistic',header=TRUE) > a<-table.element(a,myl.1,header=TRUE) > a<-table.element(a,myl.2,header=TRUE) > a<-table.element(a,'Q1',header=TRUE) > a<-table.element(a,'Estimate',header=TRUE) > a<-table.element(a,'Q3',header=TRUE) > a<-table.element(a,myl.3,header=TRUE) > a<-table.element(a,myl.4,header=TRUE) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,'IQR',header=TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'mean',header=TRUE) > q1 <- quantile(r$t[,1],0.25)[[1]] > q3 <- quantile(r$t[,1],0.75)[[1]] > p01 <- quantile(r$t[,1],myq.1)[[1]] > p05 <- quantile(r$t[,1],myq.2)[[1]] > p95 <- quantile(r$t[,1],myq.3)[[1]] > p99 <- quantile(r$t[,1],myq.4)[[1]] > a<-table.element(a,signif(p01,par2)) > a<-table.element(a,signif(p05,par2)) > a<-table.element(a,signif(q1,par2)) > a<-table.element(a,signif(r$t0[1],par2)) > a<-table.element(a,signif(q3,par2)) > a<-table.element(a,signif(p95,par2)) > a<-table.element(a,signif(p99,par2)) > a<-table.element( a,signif( sqrt(var(r$t[,1])),par2 ) ) > a<-table.element(a,signif(q3-q1,par2)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'median',header=TRUE) > q1 <- quantile(r$t[,2],0.25)[[1]] > q3 <- quantile(r$t[,2],0.75)[[1]] > p01 <- quantile(r$t[,2],myq.1)[[1]] > p05 <- quantile(r$t[,2],myq.2)[[1]] > p95 <- quantile(r$t[,2],myq.3)[[1]] > p99 <- quantile(r$t[,2],myq.4)[[1]] > a<-table.element(a,signif(p01,par2)) > a<-table.element(a,signif(p05,par2)) > a<-table.element(a,signif(q1,par2)) > a<-table.element(a,signif(r$t0[2],par2)) > a<-table.element(a,signif(q3,par2)) > a<-table.element(a,signif(p95,par2)) > a<-table.element(a,signif(p99,par2)) > a<-table.element(a,signif(sqrt(var(r$t[,2])),par2)) > a<-table.element(a,signif(q3-q1,par2)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'midrange',header=TRUE) > q1 <- quantile(r$t[,3],0.25)[[1]] > q3 <- quantile(r$t[,3],0.75)[[1]] > p01 <- quantile(r$t[,3],myq.1)[[1]] > p05 <- quantile(r$t[,3],myq.2)[[1]] > p95 <- quantile(r$t[,3],myq.3)[[1]] > p99 <- quantile(r$t[,3],myq.4)[[1]] > a<-table.element(a,signif(p01,par2)) > a<-table.element(a,signif(p05,par2)) > a<-table.element(a,signif(q1,par2)) > a<-table.element(a,signif(r$t0[3],par2)) > a<-table.element(a,signif(q3,par2)) > a<-table.element(a,signif(p95,par2)) > a<-table.element(a,signif(p99,par2)) > a<-table.element(a,signif(sqrt(var(r$t[,3])),par2)) > a<-table.element(a,signif(q3-q1,par2)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'mode',header=TRUE) > q1 <- quantile(r$t[,4],0.25)[[1]] > q3 <- quantile(r$t[,4],0.75)[[1]] > p01 <- quantile(r$t[,4],myq.1)[[1]] > p05 <- quantile(r$t[,4],myq.2)[[1]] > p95 <- quantile(r$t[,4],myq.3)[[1]] > p99 <- quantile(r$t[,4],myq.4)[[1]] > a<-table.element(a,signif(p01,par2)) > a<-table.element(a,signif(p05,par2)) > a<-table.element(a,signif(q1,par2)) > a<-table.element(a,signif(r$t0[4],par2)) > a<-table.element(a,signif(q3,par2)) > a<-table.element(a,signif(p95,par2)) > a<-table.element(a,signif(p99,par2)) > a<-table.element(a,signif(sqrt(var(r$t[,4])),par2)) > a<-table.element(a,signif(q3-q1,par2)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'mode k.dens',header=TRUE) > q1 <- quantile(r$t[,5],0.25)[[1]] > q3 <- quantile(r$t[,5],0.75)[[1]] > p01 <- quantile(r$t[,5],myq.1)[[1]] > p05 <- quantile(r$t[,5],myq.2)[[1]] > p95 <- quantile(r$t[,5],myq.3)[[1]] > p99 <- quantile(r$t[,5],myq.4)[[1]] > a<-table.element(a,signif(p01,par2)) > a<-table.element(a,signif(p05,par2)) > a<-table.element(a,signif(q1,par2)) > a<-table.element(a,signif(r$t0[5],par2)) > a<-table.element(a,signif(q3,par2)) > a<-table.element(a,signif(p95,par2)) > a<-table.element(a,signif(p99,par2)) > a<-table.element(a,signif(sqrt(var(r$t[,5])),par2)) > a<-table.element(a,signif(q3-q1,par2)) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/12croh1448965915.tab") > > try(system("convert tmp/1cidc1448965915.ps tmp/1cidc1448965915.png",intern=TRUE)) character(0) > try(system("convert tmp/254v51448965915.ps tmp/254v51448965915.png",intern=TRUE)) character(0) > try(system("convert tmp/3dk2k1448965915.ps tmp/3dk2k1448965915.png",intern=TRUE)) character(0) > try(system("convert tmp/4g8u51448965915.ps tmp/4g8u51448965915.png",intern=TRUE)) character(0) > try(system("convert tmp/53zd01448965915.ps tmp/53zd01448965915.png",intern=TRUE)) character(0) > try(system("convert tmp/68gj41448965915.ps tmp/68gj41448965915.png",intern=TRUE)) character(0) > try(system("convert tmp/79yzh1448965915.ps tmp/79yzh1448965915.png",intern=TRUE)) character(0) > try(system("convert tmp/8lggg1448965915.ps tmp/8lggg1448965915.png",intern=TRUE)) character(0) > try(system("convert tmp/9q93y1448965915.ps tmp/9q93y1448965915.png",intern=TRUE)) character(0) > try(system("convert tmp/10wbgf1448965915.ps tmp/10wbgf1448965915.png",intern=TRUE)) character(0) > try(system("convert tmp/11zlox1448965915.ps tmp/11zlox1448965915.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 7.439 0.762 8.240