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Author's title

Author*Unverified author*
R Software Modulerwasp_bootstrapplot.wasp
Title produced by softwareBlocked Bootstrap Plot - Central Tendency
Date of computationTue, 24 Apr 2012 13:55:15 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Apr/24/t1335290167segimltf3735ko4.htm/, Retrieved Fri, 03 May 2024 07:31:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=164756, Retrieved Fri, 03 May 2024 07:31:55 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact166
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bootstrap Plot - Central Tendency] [OPG7 OEF1 (3)] [2012-04-24 17:44:06] [aedd9af56bfe2946a9f9da3d899aa64c]
- RMPD    [Blocked Bootstrap Plot - Central Tendency] [OPG7 OEF2] [2012-04-24 17:55:15] [2d897010b3abf24abba169db0d9c5a05] [Current]
- R PD      [Blocked Bootstrap Plot - Central Tendency] [OPG7 OEF2(2)] [2012-04-24 17:56:58] [aedd9af56bfe2946a9f9da3d899aa64c]
-   P         [Blocked Bootstrap Plot - Central Tendency] [OPG7 OEF2(3)] [2012-04-24 17:58:14] [aedd9af56bfe2946a9f9da3d899aa64c]
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Dataseries X:
67,22
67,31
67,14
67,22
67,17
67,27
67,27
67,27
67,48
67,38
67,22
67,2
67,2
67,19
67,32
67,61
67,85
67,74
67,74
67,61
67,85
67,89
67,97
67,94
67,94
68,07
67,85
67,84
67,89
67,86
67,86
67,89
67,7
68,05
68,18
68,19
68,19
68,27
68,22
68,14
68,36
68,34
68,34
68,24
68,14
68,23
68,09
68,03
68,03
67,89
67,63
67,61
67,41
67,29
67,29
67,49
67,68
68,05
67,7
67,86




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164756&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164756&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164756&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'Gertrude Mary Cox' @ cox.wessa.net







Estimation Results of Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean67.65762567.748333333333367.8443750.1402033091709830.186750000000004
median67.6967.8567.890.2116557900681860.200000000000003
midrange67.732567.7567.761250.05678000869809310.0287500000000165

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 67.657625 & 67.7483333333333 & 67.844375 & 0.140203309170983 & 0.186750000000004 \tabularnewline
median & 67.69 & 67.85 & 67.89 & 0.211655790068186 & 0.200000000000003 \tabularnewline
midrange & 67.7325 & 67.75 & 67.76125 & 0.0567800086980931 & 0.0287500000000165 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164756&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]67.657625[/C][C]67.7483333333333[/C][C]67.844375[/C][C]0.140203309170983[/C][C]0.186750000000004[/C][/ROW]
[ROW][C]median[/C][C]67.69[/C][C]67.85[/C][C]67.89[/C][C]0.211655790068186[/C][C]0.200000000000003[/C][/ROW]
[ROW][C]midrange[/C][C]67.7325[/C][C]67.75[/C][C]67.76125[/C][C]0.0567800086980931[/C][C]0.0287500000000165[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164756&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164756&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
mean67.65762567.748333333333367.8443750.1402033091709830.186750000000004
median67.6967.8567.890.2116557900681860.200000000000003
midrange67.732567.7567.761250.05678000869809310.0287500000000165



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')