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)

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> x <- c(1747,1245,1182,958,1000,1044,875,939,736,905,796,372,1326,668,962,912,1119,891,931,1047,982,1098,714,128,1784,828,1199,1095,977,1338,975,840,1324,1236,883,177,2186,809,1434,1365,1247,1476,1211,990,1205,1238,952,204,2135,1157,1290,1071,1169,1431,945,1034,1100,1297,921,236,1990,966,1326,908,1206,1861,929,1296,1332,1352,1040,148,2090,1435,1124,1319,1436,1774,1566,1385,1147,1274,625,52,1990,1154,954,887,825,966,954,770,1838,1371,589,116,1898,712,1175,1240,1329,1550,1201,938,1030,1060,1035,635,2565,910,1304,1331,1681,1983,1021,1061,1292,1274,1024,568,2570,1125,1600,1492,2492,3523,990,869,1310,979,1244,442,2956,1055,2004,1462,1144,1454,1538,1388,1547,1570,1535,1352,1888,999,1158,1342,1443,1519,1267,1454,987,1430,1254,734)
> par4 = 'P1 P5 Q1 Q3 P95 P99'
> par3 = '5'
> par2 = '12'
> par1 = '500'
> par4 <- 'P1 P5 Q1 Q3 P95 P99'
> par3 <- '5'
> par2 <- '12'
> par1 <- '500'
> #'GNU S' R Code compiled by R2WASP v. 1.2.327 (Mon, 05 Oct 2015 17:06:50 +0100)
> #Author: root
> #To cite this work: Wessa P., (2015), Blocked Bootstrap Plot for Central Tendency (v1.0.5) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_bootstrapplot.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #
> par1 <- as.numeric(par1)
> par2 <- as.numeric(par2)
> par3 <- as.numeric(par3)
> if (par1 < 10) par1 = 10
> if (par1 > 5000) par1 = 5000
> if (par2 < 3) par2 = 3
> if (par2 > length(x)) par2 = length(x)
> 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)
+ {
+ s.mean <- mean(s)
+ s.median <- median(s)
+ s.midrange <- (max(s) + min(s)) / 2
+ s.mode <- mlv(s,method='mfv')$M
+ s.kernelmode <- mlv(s, method='kernel')$M
+ c(s.mean, s.median, s.midrange, s.mode, s.kernelmode)
+ }
> (r <- tsboot(x, boot.stat, R=par1, l=12, sim='fixed'))

BLOCK BOOTSTRAP FOR TIME SERIES

Fixed Block Length of 12 

Call:
tsboot(tseries = x, statistic = boot.stat, R = par1, l = 12, 
    sim = "fixed")


Bootstrap Statistics :
    original      bias    std. error
t1* 1206.821    2.836513    51.55483
t2* 1163.500    7.603000    62.05042
t3* 1787.500 -123.161000   206.68321
t4* 1288.250  -75.539650   223.17132
t5* 1132.598   -2.156549    85.59430
Warning messages:
1: 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
2: 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
3: 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
4: 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
5: 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
6: 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
7: 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
8: 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/1hnlv1449437874.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(r$t[,1],type='p',ylab='simulated values',main='Simulation of Mean')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/2zbts1449437874.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(r$t[,2],type='p',ylab='simulated values',main='Simulation of Median')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/31lgi1449437874.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(r$t[,3],type='p',ylab='simulated values',main='Simulation of Midrange')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/4xchi1449437874.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(r$t[,4],type='p',ylab='simulated values',main='Simulation of Mode')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/581no1449437874.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(r$t[,5],type='p',ylab='simulated values',main='Simulation of Mode of Kernel Density')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/60gqz1449437874.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> densityplot(~r$t[,1],col='black',main='Density Plot',xlab='mean')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/7jb7o1449437874.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> densityplot(~r$t[,2],col='black',main='Density Plot',xlab='median')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/8ng1s1449437874.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> densityplot(~r$t[,3],col='black',main='Density Plot',xlab='midrange')
> dev.off()
null device 
          1 
> z <- data.frame(cbind(r$t[,1],r$t[,2],r$t[,3],r$t[,4],r$t[,5]) )
> colnames(z) <- list('mean','median','midrange','mode','mode.k.dens')
> postscript(file="/var/wessaorg/rcomp/tmp/9trzh1449437874.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> boxplot(z,notch=TRUE,ylab='simulated values',main='Bootstrap Simulation - Central Tendency')
Warning message:
In bxp(list(stats = c(1093.34615384615, 1175.72115384615, 1211.26602564103,  :
  some notches went outside hinges ('box'): maybe set notch=FALSE
> grid()
> dev.off()
null device 
          1 
> if (par4 == 'P1 P5 Q1 Q3 P95 P99') {
+ myq.1 <- 0.01
+ myq.2 <- 0.05
+ myq.3 <- 0.95
+ myq.4 <- 0.99
+ myl.1 <- 'P1'
+ myl.2 <- 'P5'
+ myl.3 <- 'P95'
+ myl.4 <- 'P99'
+ }
> if (par4 == 'P0.5 P2.5 Q1 Q3 P97.5 P99.5') {
+ myq.1 <- 0.005
+ myq.2 <- 0.025
+ myq.3 <- 0.975
+ myq.4 <- 0.995
+ myl.1 <- 'P0.5'
+ myl.2 <- 'P2.5'
+ myl.3 <- 'P97.5'
+ myl.4 <- 'P99.5'
+ }
> if (par4 == 'P10 P20 Q1 Q3 P80 P90') {
+ myq.1 <- 0.10
+ myq.2 <- 0.20
+ myq.3 <- 0.80
+ myq.4 <- 0.90
+ myl.1 <- 'P10'
+ myl.2 <- 'P20'
+ myl.3 <- 'P80'
+ myl.4 <- 'P90'
+ }
> 
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
> 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Estimation Results of Blocked Bootstrap',10,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'statistic',header=TRUE)
> a<-table.element(a,myl.1,header=TRUE)
> a<-table.element(a,myl.2,header=TRUE)
> a<-table.element(a,'Q1',header=TRUE)
> a<-table.element(a,'Estimate',header=TRUE)
> a<-table.element(a,'Q3',header=TRUE)
> a<-table.element(a,myl.3,header=TRUE)
> a<-table.element(a,myl.4,header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'IQR',header=TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'mean',header=TRUE)
> q1 <- quantile(r$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$t[,1],myq.4)[[1]]
> a<-table.element(a,signif(p01,par3))
> a<-table.element(a,signif(p05,par3))
> a<-table.element(a,signif(q1,par3))
> a<-table.element(a,signif(r$t0[1],par3))
> a<-table.element(a,signif(q3,par3))
> a<-table.element(a,signif(p95,par3))
> a<-table.element(a,signif(p99,par3))
> a<-table.element( a,signif( sqrt(var(r$t[,1])),par3 ) )
> a<-table.element(a,signif(q3-q1,par3))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'median',header=TRUE)
> q1 <- quantile(r$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$t[,2],myq.4)[[1]]
> a<-table.element(a,signif(p01,par3))
> a<-table.element(a,signif(p05,par3))
> a<-table.element(a,signif(q1,par3))
> a<-table.element(a,signif(r$t0[2],par3))
> a<-table.element(a,signif(q3,par3))
> a<-table.element(a,signif(p95,par3))
> a<-table.element(a,signif(p99,par3))
> a<-table.element(a,signif(sqrt(var(r$t[,2])),par3))
> a<-table.element(a,signif(q3-q1,par3))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'midrange',header=TRUE)
> q1 <- quantile(r$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$t[,3],myq.4)[[1]]
> a<-table.element(a,signif(p01,par3))
> a<-table.element(a,signif(p05,par3))
> a<-table.element(a,signif(q1,par3))
> a<-table.element(a,signif(r$t0[3],par3))
> a<-table.element(a,signif(q3,par3))
> a<-table.element(a,signif(p95,par3))
> a<-table.element(a,signif(p99,par3))
> a<-table.element(a,signif(sqrt(var(r$t[,3])),par3))
> a<-table.element(a,signif(q3-q1,par3))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'mode',header=TRUE)
> q1 <- quantile(r$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$t[,4],myq.4)[[1]]
> a<-table.element(a,signif(p01,par3))
> a<-table.element(a,signif(p05,par3))
> a<-table.element(a,signif(q1,par3))
> a<-table.element(a,signif(r$t0[4],par3))
> a<-table.element(a,signif(q3,par3))
> a<-table.element(a,signif(p95,par3))
> a<-table.element(a,signif(p99,par3))
> a<-table.element(a,signif(sqrt(var(r$t[,4])),par3))
> a<-table.element(a,signif(q3-q1,par3))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'mode k.dens',header=TRUE)
> q1 <- quantile(r$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$t[,5],myq.4)[[1]]
> a<-table.element(a,signif(p01,par3))
> a<-table.element(a,signif(p05,par3))
> a<-table.element(a,signif(q1,par3))
> a<-table.element(a,signif(r$t0[5],par3))
> a<-table.element(a,signif(q3,par3))
> a<-table.element(a,signif(p95,par3))
> a<-table.element(a,signif(p99,par3))
> a<-table.element(a,signif(sqrt(var(r$t[,5])),par3))
> a<-table.element(a,signif(q3-q1,par3))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/10i2ah1449437874.tab") 
> 
> try(system("convert tmp/1hnlv1449437874.ps tmp/1hnlv1449437874.png",intern=TRUE))
character(0)
> try(system("convert tmp/2zbts1449437874.ps tmp/2zbts1449437874.png",intern=TRUE))
character(0)
> try(system("convert tmp/31lgi1449437874.ps tmp/31lgi1449437874.png",intern=TRUE))
character(0)
> try(system("convert tmp/4xchi1449437874.ps tmp/4xchi1449437874.png",intern=TRUE))
character(0)
> try(system("convert tmp/581no1449437874.ps tmp/581no1449437874.png",intern=TRUE))
character(0)
> try(system("convert tmp/60gqz1449437874.ps tmp/60gqz1449437874.png",intern=TRUE))
character(0)
> try(system("convert tmp/7jb7o1449437874.ps tmp/7jb7o1449437874.png",intern=TRUE))
character(0)
> try(system("convert tmp/8ng1s1449437874.ps tmp/8ng1s1449437874.png",intern=TRUE))
character(0)
> try(system("convert tmp/9trzh1449437874.ps tmp/9trzh1449437874.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
 12.342   0.599  12.972