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Author*The author of this computation has been verified*
R Software Modulerwasp_bootstrapplot.wasp
Title produced by softwareBlocked Bootstrap Plot - Central Tendency
Date of computationWed, 17 Dec 2008 13:42:46 -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/2008/Dec/17/t1229546630ri7s2gh9plzftqk.htm/, Retrieved Sun, 19 May 2024 05:38:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=34545, Retrieved Sun, 19 May 2024 05:38:59 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact152
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Blocked Bootstrap Plot - Central Tendency] [Blocked Bootstrap...] [2008-12-17 20:42:46] [0ebe94bd950a0b1969e8ed777006e521] [Current]
- RMPD    [Variability] [verbetering - opg...] [2009-01-26 16:36:39] [a18c43c8b63fa6800a53bb187b9ddd45]
-           [Variability] [Maxime Jonckheere...] [2009-05-27 21:36:38] [74be16979710d4c4e7c6647856088456]
-    D    [Blocked Bootstrap Plot - Central Tendency] [Maxime Jonckheere...] [2009-05-13 19:05:51] [74be16979710d4c4e7c6647856088456]
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Dataseries X:
66,2
66,2
66,2
66,08
66,31
66,39
66,37
66,23
66,27
66,27
66,27
66,28
66,28
66,28
66,26
66,13
65,86
65,9
65,94
65,94
65,91
65,95
65,91
66,08
66,47
66,47
66,56
66,78
67,08
67,28
67,27
67,27
67,26
67,37
67,5
67,63
67,64
67,64
67,71
67,87
67,93
68,33
68,39
68,39
68,58
68,44
68,49
68,52
68,54
68,54
68,54
68,62
68,75
68,71
68,72
68,72
68,72
68,92
68,9
69,12
69,09
69,09
69,1
69,16
68,83
68,52
68,53
68,53
68,51
68,38
68,44
68,41
68,42
68,42
68,45
68,63
68,84
68,72
68,37
68,37
68,47
68,69
68,46
68,17
68,17




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=34545&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=34545&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34545&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
mean67.390382352941267.646470588235367.97182352941180.4293165971670140.581441176470591
median67.402568.1768.420.7080095986896891.01750000000000
midrange67.4967.5167.5350.1074761008080310.0449999999999875

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 67.3903823529412 & 67.6464705882353 & 67.9718235294118 & 0.429316597167014 & 0.581441176470591 \tabularnewline
median & 67.4025 & 68.17 & 68.42 & 0.708009598689689 & 1.01750000000000 \tabularnewline
midrange & 67.49 & 67.51 & 67.535 & 0.107476100808031 & 0.0449999999999875 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34545&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]67.3903823529412[/C][C]67.6464705882353[/C][C]67.9718235294118[/C][C]0.429316597167014[/C][C]0.581441176470591[/C][/ROW]
[ROW][C]median[/C][C]67.4025[/C][C]68.17[/C][C]68.42[/C][C]0.708009598689689[/C][C]1.01750000000000[/C][/ROW]
[ROW][C]midrange[/C][C]67.49[/C][C]67.51[/C][C]67.535[/C][C]0.107476100808031[/C][C]0.0449999999999875[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34545&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34545&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
mean67.390382352941267.646470588235367.97182352941180.4293165971670140.581441176470591
median67.402568.1768.420.7080095986896891.01750000000000
midrange67.4967.5167.5350.1074761008080310.0449999999999875



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')