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Author*Unverified author*
R Software Modulerwasp_bootstrapplot.wasp
Title produced by softwareBlocked Bootstrap Plot - Central Tendency
Date of computationTue, 22 Nov 2011 05:07:10 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Nov/22/t1321956514u3do36s4u4pnnrv.htm/, Retrieved Fri, 29 Mar 2024 14:04:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=146108, Retrieved Fri, 29 Mar 2024 14:04:42 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W22
Estimated Impact84
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Blocked Bootstrap Plot - Central Tendency] [Gemiddelde consum...] [2011-11-22 10:07:10] [08802a004a000ae20ac4145e9a22f7e4] [Current]
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Dataseries X:
15.14
14.2
13.83
14.31
14.04
14.9
14.92
15.36
15.5
15.65
16.18
15.44
15.58
15.24
15.33
16.07
15.82
15.87
15.72
17.07
16.83
17.52
17.76
17.36
17.95
16.71
17.14
16.72
17.26
17.24
17.69
18.13
18.08
18.18
18.18
17.64
17.89
16.82
16.61
16.66
17.02
16.91
17.18
18.06
17.58
17.48
17.54
17.44
17.79
16.79
16.19
16.62
16.39
16.54
17.26
18
17.29
18.16
17.82
17.48
18.31
17.04
17.03
16.97
17.11
17.12
17.69
18.5
18.27
18.45
18.35
18.03
18.49
18.07
17.8
17.88
18.12
18.68
18.8
19.64
19.56
19.3
20.07
19.82
20.29
19.36
18.74
18.87
18.87
18.91
19.31
20.06
20.72
20.42
20.58
20.58
21.18
19.87
19.83
19.48
19.49
19.4
19.89
20.44
20.07
19.75
19.54
19.07
19.55
18.01
17.5
17.41
17.47
17.6
17.64
18.3
18.27
17.99
18.04
17.62
18.22
17.67
17.73
17.99
18.15
18.41
18.36
19.52
19.96
19.6
19.48
19.13




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'George Udny Yule' @ yule.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 & 4 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=146108&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=146108&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=146108&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 time4 seconds
R Server'George Udny Yule' @ yule.wessa.net







Estimation Results of Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean17.543844696969717.82969696969718.09153409090910.3752501134307530.547689393939393
median17.607517.8518.040.3410975477195660.432499999999997
midrange17.4737517.50517.6750.4347119389311120.201250000000002

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 17.5438446969697 & 17.829696969697 & 18.0915340909091 & 0.375250113430753 & 0.547689393939393 \tabularnewline
median & 17.6075 & 17.85 & 18.04 & 0.341097547719566 & 0.432499999999997 \tabularnewline
midrange & 17.47375 & 17.505 & 17.675 & 0.434711938931112 & 0.201250000000002 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=146108&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]17.5438446969697[/C][C]17.829696969697[/C][C]18.0915340909091[/C][C]0.375250113430753[/C][C]0.547689393939393[/C][/ROW]
[ROW][C]median[/C][C]17.6075[/C][C]17.85[/C][C]18.04[/C][C]0.341097547719566[/C][C]0.432499999999997[/C][/ROW]
[ROW][C]midrange[/C][C]17.47375[/C][C]17.505[/C][C]17.675[/C][C]0.434711938931112[/C][C]0.201250000000002[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=146108&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=146108&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
mean17.543844696969717.82969696969718.09153409090910.3752501134307530.547689393939393
median17.607517.8518.040.3410975477195660.432499999999997
midrange17.4737517.50517.6750.4347119389311120.201250000000002



Parameters (Session):
par1 = 200 ; par2 = 12 ;
Parameters (R input):
par1 = 200 ; 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')