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Author*Unverified author*
R Software Modulerwasp_bootstrapplot.wasp
Title produced by softwareBlocked Bootstrap Plot - Central Tendency
Date of computationSat, 08 May 2010 10:36:28 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/May/08/t1273315081bt9x4torye0qso5.htm/, Retrieved Sat, 04 May 2024 17:43:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=75657, Retrieved Sat, 04 May 2024 17:43:49 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W32
Estimated Impact191
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Blocked Bootstrap Plot - Central Tendency] [Blocked bootstrap...] [2010-05-08 10:36:28] [83074fc8d74b78a4134c1b297ef86df5] [Current]
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Dataseries X:
178600
181600
178500
176700
183500
175900
179800
186500
182700
182800
178600
183300
182900
191400
189300
192200
187900
193900
189100
193100
194800
200200
211500
202100
200300
199200
204900
207300
200000
197700
202200
200200
208300
215100
210700
208100
209000
211000
210200
205500
211400
211700
209300
207500
203300
207100
206900
228700
226900
265000
227100
228100
226500
225200
217800
221300
215300
231300
227100
237800
230200
233400
231100
237200
243700
239700
248400
241000
254500
242800
268300
253900
262100
264100
261000
269300
260400
263200
279200
272200
269200
289600
283200
284300
283000
289100
289600
289100
287400
279600
289300
295000
299600
293600
294400
290200
301000
307900
298800
310300
293900
305000
311300
317300
296200
306800
291800
301900
314600
321500
329400
311700
309700
306500
307100
301300
292200
310100
316800
284400
284600
301200
287600
314300
298200
299400
301900
265500
287100
274000
290100
263100
245200
258600
259800
269800
274600
274800
271100
257800
290300
262200
270000
290600




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=75657&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=75657&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=75657&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
mean241824.652777778249465.972222222254805.03472222212057.278697995112980.3819444445
median230962.5258200262637.521229.889619715631675
midrange250437.52526502526504463.136995066892212.5

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 241824.652777778 & 249465.972222222 & 254805.034722222 & 12057.2786979951 & 12980.3819444445 \tabularnewline
median & 230962.5 & 258200 & 262637.5 & 21229.8896197156 & 31675 \tabularnewline
midrange & 250437.5 & 252650 & 252650 & 4463.13699506689 & 2212.5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=75657&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]241824.652777778[/C][C]249465.972222222[/C][C]254805.034722222[/C][C]12057.2786979951[/C][C]12980.3819444445[/C][/ROW]
[ROW][C]median[/C][C]230962.5[/C][C]258200[/C][C]262637.5[/C][C]21229.8896197156[/C][C]31675[/C][/ROW]
[ROW][C]midrange[/C][C]250437.5[/C][C]252650[/C][C]252650[/C][C]4463.13699506689[/C][C]2212.5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=75657&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=75657&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
mean241824.652777778249465.972222222254805.03472222212057.278697995112980.3819444445
median230962.5258200262637.521229.889619715631675
midrange250437.52526502526504463.136995066892212.5



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')