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Author*Unverified author*
R Software Modulerwasp_bootstrapplot.wasp
Title produced by softwareBlocked Bootstrap Plot - Central Tendency
Date of computationTue, 02 Jun 2009 10:19:42 -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/Jun/02/t124395960195dxjpym0f5ypie.htm/, Retrieved Thu, 09 May 2024 20:47:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=41301, Retrieved Thu, 09 May 2024 20:47:37 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact142
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Blocked Bootstrap Plot - Central Tendency] [Kempeneers Liesbe...] [2009-05-17 11:08:11] [e255d5a164a6c4031b5d890e3ed09f74]
-   PD    [Blocked Bootstrap Plot - Central Tendency] [] [2009-06-02 16:19:42] [d41d8cd98f00b204e9800998ecf8427e] [Current]
-   PD      [Blocked Bootstrap Plot - Central Tendency] [Yelle Eyckmans] [2009-06-06 10:41:06] [74be16979710d4c4e7c6647856088456]
-   PD        [Blocked Bootstrap Plot - Central Tendency] [Yelle Eyckmans] [2009-06-06 10:43:02] [74be16979710d4c4e7c6647856088456]
-   P           [Blocked Bootstrap Plot - Central Tendency] [Yelle Eyckmans] [2009-06-06 10:44:49] [74be16979710d4c4e7c6647856088456]
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Dataseries X:
3851,3
3851,8
3854,1
3858,4
3861,6
3856,3
3855,8
3860,4
3855,1
3839,5
3833
3833,6
3826,8
3818,2
3811,4
3806,8
3810,3
3818,2
3858,9
3867,8
3872,3
3873,3
3876,7
3882,6
3883,5
3882,2
3888,1
3893,7
3901,9
3914,3
3930,3
3948,3
3971,5
3990,1
3993
3998
4015,8
4041,2
4060,7
4076,7
4103
4125,3
4139,7
4146,7
4158
4155,1
4144,8
4148,2
4142,5
4142,1
4145,4
4146,3
4143,5
4149,2
4158,9
4166,1
4179,1
4194,4
4211,7
4226,3
4235,8
4243,6
4258,7
4278,2
4298
4315,1
4334,3
4356
4374
4395,5
4417,8
4432,8
4446,3




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=41301&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=41301&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41301&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 time2 seconds
R Server'George Udny Yule' @ 72.249.76.132







Estimation Results of Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean3998.302739726034044.327397260274093.6955479452169.681497718277395.3928082191778
median3901.94015.84143.5115.182337929277241.6
midrange4100.96254126.554132.2546.165118245822331.2875000000004

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 3998.30273972603 & 4044.32739726027 & 4093.69554794521 & 69.6814977182773 & 95.3928082191778 \tabularnewline
median & 3901.9 & 4015.8 & 4143.5 & 115.182337929277 & 241.6 \tabularnewline
midrange & 4100.9625 & 4126.55 & 4132.25 & 46.1651182458223 & 31.2875000000004 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=41301&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]3998.30273972603[/C][C]4044.32739726027[/C][C]4093.69554794521[/C][C]69.6814977182773[/C][C]95.3928082191778[/C][/ROW]
[ROW][C]median[/C][C]3901.9[/C][C]4015.8[/C][C]4143.5[/C][C]115.182337929277[/C][C]241.6[/C][/ROW]
[ROW][C]midrange[/C][C]4100.9625[/C][C]4126.55[/C][C]4132.25[/C][C]46.1651182458223[/C][C]31.2875000000004[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=41301&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41301&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
mean3998.302739726034044.327397260274093.6955479452169.681497718277395.3928082191778
median3901.94015.84143.5115.182337929277241.6
midrange4100.96254126.554132.2546.165118245822331.2875000000004



Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;
Parameters (R input):
par1 = 200 ; 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')