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Author*Unverified author*
R Software Modulerwasp_bootstrapplot.wasp
Title produced by softwareBlocked Bootstrap Plot - Central Tendency
Date of computationMon, 30 Dec 2013 07:06:58 -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/Dec/30/t1388405292o5vubbs0kq832xj.htm/, Retrieved Thu, 28 Mar 2024 22:19:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232668, Retrieved Thu, 28 Mar 2024 22:19:58 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsBootstrap Plot 750simulaties voor de reeks "indexcijfers cola limonade" Valerie Weyts Karel de Grote-Hogeschool
Estimated Impact126
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bootstrap Plot - Central Tendency] [Bootstrap Plot vo...] [2013-12-29 14:51:21] [ba0d20b2fbb0c8f9ef8b1828cc8a0bda]
- RMPD    [Blocked Bootstrap Plot - Central Tendency] [Bootstrap Plot 75...] [2013-12-30 12:06:58] [feb2df3f24188fb89c42f3077ec68a56] [Current]
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Dataseries X:
100.17
101.13
99.25
99.69
101.04
99.79
100.35
101.45
100.4
100.52
102.52
101.23
102.14
101.06
100.31
101.18
101.28
101.99
101.34
100.5
103.74
104.19
102.23
103.32
104.67
103.22
102.64
105.26
103.63
102.71
104.34
102.92
105.92
107.39
105.68
105.86
107.05
106.77
105.88
106.23
107.53
105.51
107.37
105.61
108.38
109.6
106.62
105.69
107.06
105.67
106.24
107.9
105.91
106.44
107.69
105.9
108.59
111.36
109.36
109.21
111.3
109.21
110.95
110.89
111.04
108.96
110.5
109.02
112.87
112.73
113.28
113.53
112.99
112.68
114.26
114.28
114.28
114.2
113.64
114.2
116.68
116.73
118.71
117.8




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time11 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 11 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232668&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]11 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232668&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232668&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 time11 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







Estimation Results of Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean105.851398809524106.825714285714108.021251.52937810949682.16985119047621
median105.67106.075107.612.133952793101681.94
midrange107.99108.98108.981.205905487679620.989999999999981

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 105.851398809524 & 106.825714285714 & 108.02125 & 1.5293781094968 & 2.16985119047621 \tabularnewline
median & 105.67 & 106.075 & 107.61 & 2.13395279310168 & 1.94 \tabularnewline
midrange & 107.99 & 108.98 & 108.98 & 1.20590548767962 & 0.989999999999981 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232668&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]105.851398809524[/C][C]106.825714285714[/C][C]108.02125[/C][C]1.5293781094968[/C][C]2.16985119047621[/C][/ROW]
[ROW][C]median[/C][C]105.67[/C][C]106.075[/C][C]107.61[/C][C]2.13395279310168[/C][C]1.94[/C][/ROW]
[ROW][C]midrange[/C][C]107.99[/C][C]108.98[/C][C]108.98[/C][C]1.20590548767962[/C][C]0.989999999999981[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232668&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232668&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
mean105.851398809524106.825714285714108.021251.52937810949682.16985119047621
median105.67106.075107.612.133952793101681.94
midrange107.99108.98108.981.205905487679620.989999999999981



Parameters (Session):
par1 = 750 ; par2 = 12 ;
Parameters (R input):
par1 = 750 ; par2 = 12 ;
R code (references can be found in the software module):
par2 <- '12'
par1 <- '200'
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')