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Author*Unverified author*
R Software Modulerwasp_bootstrapplot.wasp
Title produced by softwareBlocked Bootstrap Plot - Central Tendency
Date of computationThu, 13 Aug 2009 03:41:40 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Aug/13/t1250156532odco2tij9wjgs7b.htm/, Retrieved Thu, 31 Oct 2024 22:58:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=42593, Retrieved Thu, 31 Oct 2024 22:58:43 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact250
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Blocked Bootstrap Plot - Central Tendency] [50 simulaties Hot...] [2009-08-13 09:41:40] [768ad88abce8b6ce0be22cfe8ac9beaf] [Current]
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Dataseries X:
613,20
614,70
618,40
628,20
629,00
629,70
630,40
630,40
639,30
639,40
640,90
640,80
642,10
645,30
647,60
648,40
648,80
648,90
648,90
648,90
650,30
650,30
650,00
650,00
650,50
658,40
666,00
675,50
680,70
690,60
690,60
691,10
692,90
693,80
692,80
697,50
699,00
702,10
704,80
715,50
721,80
726,40
727,70
727,40
731,30
734,40
733,40
733,40
738,10
742,60
747,20
751,10
752,60
758,90
759,10
764,30
765,60
767,60
767,60
765,60
768,20
770,90
775,10
777,60
778,60
778,90
779,40
779,90
781,70
789,10
788,70
788,80
790,80
794,10
795,10
797,30
803,80
805,60
804,60
804,50
805,80
806,80
805,20
814,90
816,60
819,50
823,00
824,00
831,40
831,70
831,10
832,10
833,30
838,80
838,00
837,30
994,20
994,20
994,20
994,20
994,20
1092,60
1100,00
1100,00
1092,60
1000,70
1000,70
1000,50
1000,50
1000,50
1000,50
1000,50
1000,50
1087,70
1113,20
1116,00
1085,20
1031,30
1028,70
1027,50
1027,50
1027,50
1027,50
1027,50
1027,50
1152,20
1155,30
1154,00
1119,90
1079,30
1074,30
1069,80




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=42593&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=42593&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=42593&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
mean792.882954545455818.079545454545858.23674242424241.875726630179365.3537878787879
median759.1779.15813.512549.678206325042354.4125
midrange883.7625884.25884.2520.65115564785260.487499999999955

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 792.882954545455 & 818.079545454545 & 858.236742424242 & 41.8757266301793 & 65.3537878787879 \tabularnewline
median & 759.1 & 779.15 & 813.5125 & 49.6782063250423 & 54.4125 \tabularnewline
midrange & 883.7625 & 884.25 & 884.25 & 20.6511556478526 & 0.487499999999955 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=42593&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]792.882954545455[/C][C]818.079545454545[/C][C]858.236742424242[/C][C]41.8757266301793[/C][C]65.3537878787879[/C][/ROW]
[ROW][C]median[/C][C]759.1[/C][C]779.15[/C][C]813.5125[/C][C]49.6782063250423[/C][C]54.4125[/C][/ROW]
[ROW][C]midrange[/C][C]883.7625[/C][C]884.25[/C][C]884.25[/C][C]20.6511556478526[/C][C]0.487499999999955[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=42593&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=42593&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
mean792.882954545455818.079545454545858.23674242424241.875726630179365.3537878787879
median759.1779.15813.512549.678206325042354.4125
midrange883.7625884.25884.2520.65115564785260.487499999999955



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')