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Author's title

Author

*Unverified author*

R Software Module

rwasp_bootstrapplot.wasp

Title produced by software

Blocked Bootstrap Plot - Central Tendency

Date of computation

Tue, 21 May 2013 09:06:56 -0400

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/May/21/t1369141639ym5n9hdnrvf76xe.htm/, Retrieved Wed, 01 May 2024 23:39:40 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=209195, Retrieved Wed, 01 May 2024 23:39:40 +0000

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Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Blocked Bootstrap Plot - Central Tendency] [bootstrap Plot 50...] [2013-05-21 13:06:56] [4772101fb1e8fea1eb9b6fc7ea4f009e] [Current]

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Dataseries X:

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Histogram

Boxplots

0,67
0,66
0,66
0,67
0,67
0,67
0,67
0,68
0,68
0,67
0,67
0,67
0,67
0,67
0,69
0,69
0,69
0,69
0,69
0,69
0,7
0,69
0,68
0,7
0,7
0,71
0,69
0,7
0,7
0,71
0,71
0,71
0,71
0,7
0,7
0,71
0,71
0,71
0,71
0,7
0,69
0,7
0,7
0,7
0,71
0,7
0,7
0,69
0,7
0,71
0,71
0,71
0,71
0,71
0,71
0,71
0,71
0,69
0,7
0,7
0,7
0,72
0,7
0,69
0,7
0,71
0,72
0,72
0,73
0,72
0,74
0,75

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	7 seconds
R Server	'Gwilym Jenkins' @ jenkins.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 & 7 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=209195&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]7 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=209195&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=209195&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	7 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

Estimation Results of Blocked Bootstrap
statistic	Q1	Estimate	Q3	S.D.	IQR
mean	0.693576388888889	0.697638888888889	0.700104166666667	0.00480529503966627	0.0065277777777778
median	0.69	0.7	0.7	0.00679510628230015	0.01
midrange	0.695	0.705	0.705	0.00660936256150229	0.01

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 0.693576388888889 & 0.697638888888889 & 0.700104166666667 & 0.00480529503966627 & 0.0065277777777778 \tabularnewline
median & 0.69 & 0.7 & 0.7 & 0.00679510628230015 & 0.01 \tabularnewline
midrange & 0.695 & 0.705 & 0.705 & 0.00660936256150229 & 0.01 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=209195&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]0.693576388888889[/C][C]0.697638888888889[/C][C]0.700104166666667[/C][C]0.00480529503966627[/C][C]0.0065277777777778[/C][/ROW]
[ROW][C]median[/C][C]0.69[/C][C]0.7[/C][C]0.7[/C][C]0.00679510628230015[/C][C]0.01[/C][/ROW]
[ROW][C]midrange[/C][C]0.695[/C][C]0.705[/C][C]0.705[/C][C]0.00660936256150229[/C][C]0.01[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=209195&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=209195&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
statistic	Q1	Estimate	Q3	S.D.	IQR
mean	0.693576388888889	0.697638888888889	0.700104166666667	0.00480529503966627	0.0065277777777778
median	0.69	0.7	0.7	0.00679510628230015	0.01
midrange	0.695	0.705	0.705	0.00660936256150229	0.01

Figure 1

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Postscript link

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Figure 2

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Figure 3

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Figure 4

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Figure 5

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Figure 6

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Figure 7

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Parameters (Session):

par1 = 200 ; par2 = 5 ; par3 = 0 ;

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')

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