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Author*Unverified author*
R Software Modulerwasp_bootstrapplot.wasp
Title produced by softwareBlocked Bootstrap Plot - Central Tendency
Date of computationSat, 23 Nov 2013 10:20:18 -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/2013/Nov/23/t13852200340lviqnfptl8wm1u.htm/, Retrieved Fri, 03 May 2024 00:13:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=227842, Retrieved Fri, 03 May 2024 00:13:21 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact86
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bootstrap Plot - Central Tendency] [] [2013-11-23 14:49:45] [905566a0c44f6df47d7858605d7fcf7a]
- R P   [Bootstrap Plot - Central Tendency] [] [2013-11-23 14:59:21] [905566a0c44f6df47d7858605d7fcf7a]
- RMPD      [Blocked Bootstrap Plot - Central Tendency] [] [2013-11-23 15:20:18] [c022b39ff2bb06cc8d15c2aa42c6729c] [Current]
- R PD        [Blocked Bootstrap Plot - Central Tendency] [] [2013-11-23 15:22:10] [905566a0c44f6df47d7858605d7fcf7a]
-   P           [Blocked Bootstrap Plot - Central Tendency] [] [2013-11-23 15:24:10] [905566a0c44f6df47d7858605d7fcf7a]
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Dataseries X:
26,73
26,85
27,01
27,09
27,11
27,16
27,13
27,19
27,49
27,63
27,72
27,77
27,81
27,92
28,07
28,14
28,17
28,20
28,21
28,20
28,19
28,24
28,25
28,26
28,33
28,67
28,81
28,99
29,16
29,25
29,25
29,38
29,48
29,65
29,69
29,73
29,81
30,05
30,29
30,37
30,50
30,67
30,76
30,84
30,86
31,09
31,20
31,19
31,18
31,31
31,39
31,39
31,37
31,36
31,37
31,35
31,34
31,47
31,48
31,54
31,55
31,55
31,57
31,66
31,74
31,78
31,80
31,68
31,70
31,70
31,75
31,73
31,82
31,90
31,82
31,51
31,42
30,97
30,99
30,92
30,95
30,82
30,72
30,73




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time7 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=227842&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=227842&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=227842&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 time7 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Estimation Results of Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean29.706428571428629.927261904761930.5061309523810.6082095994691980.799702380952382
median29.67530.69531.090.9283310732883251.415
midrange29.31529.31529.53750.3634728325473590.222500000000004

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 29.7064285714286 & 29.9272619047619 & 30.506130952381 & 0.608209599469198 & 0.799702380952382 \tabularnewline
median & 29.675 & 30.695 & 31.09 & 0.928331073288325 & 1.415 \tabularnewline
midrange & 29.315 & 29.315 & 29.5375 & 0.363472832547359 & 0.222500000000004 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=227842&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]29.7064285714286[/C][C]29.9272619047619[/C][C]30.506130952381[/C][C]0.608209599469198[/C][C]0.799702380952382[/C][/ROW]
[ROW][C]median[/C][C]29.675[/C][C]30.695[/C][C]31.09[/C][C]0.928331073288325[/C][C]1.415[/C][/ROW]
[ROW][C]midrange[/C][C]29.315[/C][C]29.315[/C][C]29.5375[/C][C]0.363472832547359[/C][C]0.222500000000004[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=227842&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=227842&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
mean29.706428571428629.927261904761930.5061309523810.6082095994691980.799702380952382
median29.67530.69531.090.9283310732883251.415
midrange29.31529.31529.53750.3634728325473590.222500000000004



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')