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Author*Unverified author*
R Software Modulerwasp_bootstrapplot.wasp
Title produced by softwareBlocked Bootstrap Plot - Central Tendency
Date of computationSun, 07 Jun 2009 12:43:44 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Jun/07/t1244400241s6kfn395uaaoz6u.htm/, Retrieved Mon, 13 May 2024 14:53:12 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=42229, Retrieved Mon, 13 May 2024 14:53:12 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact114
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Quartiles] [] [2009-06-07 13:46:35] [20f4bab96040345df1f930341b3cf3a9]
- RM D    [Blocked Bootstrap Plot - Central Tendency] [] [2009-06-07 18:43:44] [e921d89db97faa9283224ee60d8fb091] [Current]
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Dataseries X:
 
58.53
49.09
24.68
16.71
19.86
38.23
36.11
19.59
14.91
15.74
15.40
13.06
19.07
15.28
15.82
12.77
12.05
11.69
13.85
13.85
10.07
9.17
10.79
13.44
21.17
18.64
13.21
15.54
21.94
23.11
18.64
14.94
16.90
15.46
11.15
13.13
12.48
12.95
12.59
10.58
10.58
12.39
15.53
13.06
10.22
16.33
19.72
21.31
18.84
24.84
15.67
15.57
12.73
13.56
15.54
17.22
12.14
11.07
12.02
11.55
6.92
10.33
8.38
12.11
11.46
12.75
13.32
13.00
11.90
11.79
12.55
11.84
11.25
11.15
10.99
11.70
14.01
17.51
17.27
16.90
15.79
15.45
16.24
16.71
16.77
16.64
17.80
16.87
16.13
15.76
15.66
15.54
15.30
15.05
14.69
14.39
14.18
13.70
13.66
13.27
13.56
13.14
14.19
22.57
23.09
23.31
22.91
22.36
43.06
64.67
64.68
56.90
48.79
45.21
41.40
22.17
25.52
20.28
22.87
27.63
22.95
21.35
18.38
17.15
18.27
19.40
20.52




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 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=42229&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=42229&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=42229&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Estimation Results of Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean17.093858267716518.623149606299220.97549212598432.693212850425363.88163385826772
median14.967515.5416.331.328434340085491.36250000000000
midrange33.8535.835.83.024599047470461.95000000000000

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 17.0938582677165 & 18.6231496062992 & 20.9754921259843 & 2.69321285042536 & 3.88163385826772 \tabularnewline
median & 14.9675 & 15.54 & 16.33 & 1.32843434008549 & 1.36250000000000 \tabularnewline
midrange & 33.85 & 35.8 & 35.8 & 3.02459904747046 & 1.95000000000000 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=42229&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]17.0938582677165[/C][C]18.6231496062992[/C][C]20.9754921259843[/C][C]2.69321285042536[/C][C]3.88163385826772[/C][/ROW]
[ROW][C]median[/C][C]14.9675[/C][C]15.54[/C][C]16.33[/C][C]1.32843434008549[/C][C]1.36250000000000[/C][/ROW]
[ROW][C]midrange[/C][C]33.85[/C][C]35.8[/C][C]35.8[/C][C]3.02459904747046[/C][C]1.95000000000000[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=42229&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=42229&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
mean17.093858267716518.623149606299220.97549212598432.693212850425363.88163385826772
median14.967515.5416.331.328434340085491.36250000000000
midrange33.8535.835.83.024599047470461.95000000000000



Parameters (Session):
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')