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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 10:22:10 -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/2013/Nov/23/t1385220154v5bpx8v7t4lju9u.htm/, Retrieved Thu, 02 May 2024 23:05:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=227843, Retrieved Thu, 02 May 2024 23:05:56 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact88
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] [905566a0c44f6df47d7858605d7fcf7a]
- R PD        [Blocked Bootstrap Plot - Central Tendency] [] [2013-11-23 15:22:10] [c022b39ff2bb06cc8d15c2aa42c6729c] [Current]
-   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 time6 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 6 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=227843&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]6 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=227843&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=227843&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 time6 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net







Estimation Results of Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean29.560833333333329.927261904761930.4619940476190.5953988854366950.901160714285712
median29.6287530.69531.1851.000660756574751.55625000000001
midrange29.31529.31529.65750.3220572220450230.342500000000001

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 29.5608333333333 & 29.9272619047619 & 30.461994047619 & 0.595398885436695 & 0.901160714285712 \tabularnewline
median & 29.62875 & 30.695 & 31.185 & 1.00066075657475 & 1.55625000000001 \tabularnewline
midrange & 29.315 & 29.315 & 29.6575 & 0.322057222045023 & 0.342500000000001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=227843&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]29.5608333333333[/C][C]29.9272619047619[/C][C]30.461994047619[/C][C]0.595398885436695[/C][C]0.901160714285712[/C][/ROW]
[ROW][C]median[/C][C]29.62875[/C][C]30.695[/C][C]31.185[/C][C]1.00066075657475[/C][C]1.55625000000001[/C][/ROW]
[ROW][C]midrange[/C][C]29.315[/C][C]29.315[/C][C]29.6575[/C][C]0.322057222045023[/C][C]0.342500000000001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=227843&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=227843&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
mean29.560833333333329.927261904761930.4619940476190.5953988854366950.901160714285712
median29.6287530.69531.1851.000660756574751.55625000000001
midrange29.31529.31529.65750.3220572220450230.342500000000001



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')