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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

Thu, 21 Nov 2013 09:09:33 -0500

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/Nov/21/t13850430007g4307k3r191ha3.htm/, Retrieved Fri, 03 May 2024 11:44:40 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=227212, Retrieved Fri, 03 May 2024 11:44:40 +0000

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No (this computation is public)

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Estimated Impact

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

-       [Blocked Bootstrap Plot - Central Tendency] [] [2013-11-21 14:09:33] [ba1aac5cc07b687ee7a9bc35c791a1eb] [Current]

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Dataseries X:

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Histogram

Boxplots

2.7
3
-0.3
1.1
1.7
1.6
3
3.3
6.7
5.6
6
4.8
5.9
4.3
3.7
5.6
1.7
3.2
3.6
1.7
0.5
2.1
1.5
2.7
1.4
1.2
2.3
1.6
4.7
3.5
4.4
3.9
3.5
3
1.6
2.2
4.1
4.3
3.5
1.8
0.6
-0.4
-2.5
-1.6
-1.9
-1.6
-0.7
-1.1
0.3
1.3
3.3
2.4
2
3.9
4.2
4.9
5.8
4.8
4.4
5.3
2.1
2
-0.9
0.1
-0.5
-0.1
0.7
-0.4
-1.5
-0.3
1
0.4
0.3
1.8
3
2.2
3.4
3.4
3.1
4.5
4.6
5.7
4.3
4.5

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	8 seconds
R Server	'Sir Maurice George Kendall' @ kendall.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 & 8 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=227212&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]8 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=227212&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=227212&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	8 seconds
R Server	'Sir Maurice George Kendall' @ kendall.wessa.net

Estimation Results of Blocked Bootstrap
statistic	Q1	Estimate	Q3	S.D.	IQR
mean	2.11309523809524	2.375	2.70684523809524	0.488242118335049	0.59375
median	2.0875	2.35	3	0.607433847753798	0.9125
midrange	1.9	2.1	2.2875	0.371180295217552	0.3875

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 2.11309523809524 & 2.375 & 2.70684523809524 & 0.488242118335049 & 0.59375 \tabularnewline
median & 2.0875 & 2.35 & 3 & 0.607433847753798 & 0.9125 \tabularnewline
midrange & 1.9 & 2.1 & 2.2875 & 0.371180295217552 & 0.3875 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=227212&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]2.11309523809524[/C][C]2.375[/C][C]2.70684523809524[/C][C]0.488242118335049[/C][C]0.59375[/C][/ROW]
[ROW][C]median[/C][C]2.0875[/C][C]2.35[/C][C]3[/C][C]0.607433847753798[/C][C]0.9125[/C][/ROW]
[ROW][C]midrange[/C][C]1.9[/C][C]2.1[/C][C]2.2875[/C][C]0.371180295217552[/C][C]0.3875[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=227212&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=227212&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	2.11309523809524	2.375	2.70684523809524	0.488242118335049	0.59375
median	2.0875	2.35	3	0.607433847753798	0.9125
midrange	1.9	2.1	2.2875	0.371180295217552	0.3875

Figure 1

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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 = 12 ;

Parameters (R input):

par1 = 200 ; par2 = 12 ;

R code (references can be found in the software module):

par2 <- '12'
par1 <- '50'
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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