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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

Wed, 07 Jan 2009 07:32:23 -0700

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/2009/Jan/07/t12313387701qafdpzbssmopzb.htm/, Retrieved Sun, 05 May 2024 17:23:01 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=36787, Retrieved Sun, 05 May 2024 17:23:01 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

209

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

-     [Bootstrap Plot - Central Tendency] [Dennis Collin] [2009-01-07 14:16:12] [2097edf1f094fab6879a8cb46df74ec2]
-   P   [Bootstrap Plot - Central Tendency] [Dennis Collin] [2009-01-07 14:19:01] [2097edf1f094fab6879a8cb46df74ec2]
- RMPD      [Blocked Bootstrap Plot - Central Tendency] [Dennis Collin] [2009-01-07 14:32:23] [06e57c0cb32e2f613cf343ab1a0ac99f] [Current]
-   PD        [Blocked Bootstrap Plot - Central Tendency] [Dennis Collin] [2009-01-07 14:36:14] [2097edf1f094fab6879a8cb46df74ec2] 
-   P           [Blocked Bootstrap Plot - Central Tendency] [Dennis Collin] [2009-01-07 14:40:13] [2097edf1f094fab6879a8cb46df74ec2] 
-   PD        [Blocked Bootstrap Plot - Central Tendency] [Dennis Collin] [2009-01-07 14:56:33] [2097edf1f094fab6879a8cb46df74ec2] 
-   P           [Blocked Bootstrap Plot - Central Tendency] [Dennis Collin] [2009-01-07 14:59:41] [2097edf1f094fab6879a8cb46df74ec2] 

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Dataseries X:

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Histogram

Boxplots

1,29
1,29
1,3
1,3
1,3
1,3
1,31
1,31
1,31
1,31
1,31
1,32
1,32
1,32
1,32
1,33
1,33
1,33
1,34
1,34
1,34
1,34
1,34
1,34
1,34
1,35
1,36
1,36
1,36
1,37
1,37
1,37
1,37
1,37
1,37
1,37
1,38
1,38
1,38
1,39
1,4
1,4
1,4
1,4
1,41
1,42
1,43
1,43
1,43
1,44
1,45
1,45
1,46
1,46
1,47
1,47
1,47
1,48
1,49
1,49
1,49
1,5
1,51
1,51
1,51
1,52
1,52
1,52
1,52
1,53
1,53
1,53
1,53
1,54
1,54
1,55
1,55
1,55
1,56
1,56
1,58
1,58
1,58
1,58
1,58
1,58
1,59
1,59
1,6
1,6
1,6
1,61
1,62
1,62
1,63
1,63

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	4 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 4 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36787&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36787&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36787&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	4 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Estimation Results of Blocked Bootstrap
statistic	Q1	Estimate	Q3	S.D.	IQR
mean	1.42453125	1.44291666666667	1.47130208333333	0.0320142821534150	0.0467708333333332
median	1.39625	1.43	1.49	0.058763535132125	0.0937499999999998
midrange	1.46	1.46	1.46	0.0124030937549419	0

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 1.42453125 & 1.44291666666667 & 1.47130208333333 & 0.0320142821534150 & 0.0467708333333332 \tabularnewline
median & 1.39625 & 1.43 & 1.49 & 0.058763535132125 & 0.0937499999999998 \tabularnewline
midrange & 1.46 & 1.46 & 1.46 & 0.0124030937549419 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36787&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]1.42453125[/C][C]1.44291666666667[/C][C]1.47130208333333[/C][C]0.0320142821534150[/C][C]0.0467708333333332[/C][/ROW]
[ROW][C]median[/C][C]1.39625[/C][C]1.43[/C][C]1.49[/C][C]0.058763535132125[/C][C]0.0937499999999998[/C][/ROW]
[ROW][C]midrange[/C][C]1.46[/C][C]1.46[/C][C]1.46[/C][C]0.0124030937549419[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36787&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36787&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	1.42453125	1.44291666666667	1.47130208333333	0.0320142821534150	0.0467708333333332
median	1.39625	1.43	1.49	0.058763535132125	0.0937499999999998
midrange	1.46	1.46	1.46	0.0124030937549419	0

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 = 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')

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