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Author*Unverified author*
R Software Modulerwasp_bootstrapplot.wasp
Title produced by softwareBlocked Bootstrap Plot - Central Tendency
Date of computationSun, 24 Jan 2010 06:44:50 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Jan/24/t1264340846w1fxigfguper1bj.htm/, Retrieved Thu, 02 May 2024 19:48:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=72404, Retrieved Thu, 02 May 2024 19:48:10 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W32
Estimated Impact203
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Blocked Bootstrap Plot - Central Tendency] [] [2010-01-24 13:44:50] [6021303ec4295e707c1f24599760c44a] [Current]
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Dataseries X:
441700
448500
415600
408000
416600
409300
387600
394500
407600
378500
359600
435700
433800
427700
413300
379500
379300
353700
378200
380600
394000
374000
375000
437600
443900
488800
463900
440000
453800
451600
453400
461400
509100
540600
555100
677400
694600
750100
733900
709300
720500
693200
687200
686800
720900
653100
624700
690000
717800
736500
699900
675600
635600
632500
594900
604000
620800
578400
571200
627400
657700
674100
672800
615300
609100
607600
566900
572700
589200
534800
543100
591100
624800
665300
642600
608700
594500
563800
596100
597600
633100
591000
584200
655800
670700
699700
712900
652000
635100
603100
610100
602000
597600
585400
567100
620600
646200
644800
645200
644800
593000
569100
518800
538700
554600
507900
488400
563300
592400
598100
546300
516100
518500
477400
483400
469400
501300
457400
446700
501900
550400
593700
548900
534200
550500
541800
569300
587400
627700
607000
629500
704600
767700
812200
824600
856300
812200
764100
801700
806000
867200
801600
817500
920900
959700
997700
949100
910900
920400
914200
926300
906400
926100
902500
895300
979900
1009700
1043800
979800
921600
923500
914500
891700
916000
931700
902400
893700
941500
980100
1006900
949200
883200
849900
839200
803900
797900
830800
753300
764100
807600
853700
886200
815700
743000
753600
724800
709600
721900




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=72404&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=72404&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=72404&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Estimation Results of Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean617476.196808511652285.638297872680039.22872340443548.290303771962563.0319148937
median59815062610066800041405.350635207669850
midrange682087.569875070170020111.06612321319612.5

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 617476.196808511 & 652285.638297872 & 680039.228723404 & 43548.2903037719 & 62563.0319148937 \tabularnewline
median & 598150 & 626100 & 668000 & 41405.3506352076 & 69850 \tabularnewline
midrange & 682087.5 & 698750 & 701700 & 20111.066123213 & 19612.5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=72404&T=1

[TABLE]
[ROW][C]Estimation Results of Blocked Bootstrap[/C][/ROW]
[ROW][C]statistic[/C][C]Q1[/C][C]Estimate[/C][C]Q3[/C][C]S.D.[/C][C]IQR[/C][/ROW]
[ROW][C]mean[/C][C]617476.196808511[/C][C]652285.638297872[/C][C]680039.228723404[/C][C]43548.2903037719[/C][C]62563.0319148937[/C][/ROW]
[ROW][C]median[/C][C]598150[/C][C]626100[/C][C]668000[/C][C]41405.3506352076[/C][C]69850[/C][/ROW]
[ROW][C]midrange[/C][C]682087.5[/C][C]698750[/C][C]701700[/C][C]20111.066123213[/C][C]19612.5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=72404&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=72404&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Estimation Results of Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean617476.196808511652285.638297872680039.22872340443548.290303771962563.0319148937
median59815062610066800041405.350635207669850
midrange682087.569875070170020111.06612321319612.5



Parameters (Session):
par1 = 50 ; par2 = 12 ;
Parameters (R input):
par1 = 50 ; par2 = 12 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
if (par1 < 10) par1 = 10
if (par1 > 5000) par1 = 5000
if (par2 < 3) par2 = 3
if (par2 > length(x)) par2 = length(x)
library(lattice)
library(boot)
boot.stat <- function(s)
{
s.mean <- mean(s)
s.median <- median(s)
s.midrange <- (max(s) + min(s)) / 2
c(s.mean, s.median, s.midrange)
}
(r <- tsboot(x, boot.stat, R=par1, l=12, sim='fixed'))
bitmap(file='plot1.png')
plot(r$t[,1],type='p',ylab='simulated values',main='Simulation of Mean')
grid()
dev.off()
bitmap(file='plot2.png')
plot(r$t[,2],type='p',ylab='simulated values',main='Simulation of Median')
grid()
dev.off()
bitmap(file='plot3.png')
plot(r$t[,3],type='p',ylab='simulated values',main='Simulation of Midrange')
grid()
dev.off()
bitmap(file='plot4.png')
densityplot(~r$t[,1],col='black',main='Density Plot',xlab='mean')
dev.off()
bitmap(file='plot5.png')
densityplot(~r$t[,2],col='black',main='Density Plot',xlab='median')
dev.off()
bitmap(file='plot6.png')
densityplot(~r$t[,3],col='black',main='Density Plot',xlab='midrange')
dev.off()
z <- data.frame(cbind(r$t[,1],r$t[,2],r$t[,3]))
colnames(z) <- list('mean','median','midrange')
bitmap(file='plot7.png')
boxplot(z,notch=TRUE,ylab='simulated values',main='Bootstrap Simulation - Central Tendency')
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Estimation Results of Blocked Bootstrap',6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'statistic',header=TRUE)
a<-table.element(a,'Q1',header=TRUE)
a<-table.element(a,'Estimate',header=TRUE)
a<-table.element(a,'Q3',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'IQR',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
q1 <- quantile(r$t[,1],0.25)[[1]]
q3 <- quantile(r$t[,1],0.75)[[1]]
a<-table.element(a,q1)
a<-table.element(a,r$t0[1])
a<-table.element(a,q3)
a<-table.element(a,sqrt(var(r$t[,1])))
a<-table.element(a,q3-q1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'median',header=TRUE)
q1 <- quantile(r$t[,2],0.25)[[1]]
q3 <- quantile(r$t[,2],0.75)[[1]]
a<-table.element(a,q1)
a<-table.element(a,r$t0[2])
a<-table.element(a,q3)
a<-table.element(a,sqrt(var(r$t[,2])))
a<-table.element(a,q3-q1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'midrange',header=TRUE)
q1 <- quantile(r$t[,3],0.25)[[1]]
q3 <- quantile(r$t[,3],0.75)[[1]]
a<-table.element(a,q1)
a<-table.element(a,r$t0[3])
a<-table.element(a,q3)
a<-table.element(a,sqrt(var(r$t[,3])))
a<-table.element(a,q3-q1)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')