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Author*Unverified author*
R Software Modulerwasp_bootstrapplot.wasp
Title produced by softwareBlocked Bootstrap Plot - Central Tendency
Date of computationThu, 18 Dec 2008 13:57:48 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Dec/18/t1229633928bxdphb25bdtzdv0.htm/, Retrieved Sat, 11 May 2024 17:33:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=34947, Retrieved Sat, 11 May 2024 17:33:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact126
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Blocked Bootstrap Plot - Central Tendency] [Robbe Leys_2MAR03...] [2008-12-18 20:57:48] [5cfda051308d8cc79b9da3748118f98f] [Current]
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Dataseries X:
284.4
212.8
226.9
308.4
262
227.9
236.1
320.4
271.9
232.8
237
313.4
261.4
226.8
249.9
314.3
286.1
226.5
260.4
311.4
294.7
232.6
257.2
339.2
279.1
249.8
269.8
345.7
293.8
254.7
277.5
363.4
313.4
272.8
300.1
369.5
330.8
287.8
305.9
386.1
335.2
288
308.3
402.3
352.8
316.1
324.9
404.8
393
318.9
327
442.3
383.1
331.6
361.4
445.9
386.6
357.2
373.6
466.2
409.6
369.8
378.6
487
419.2
376.7
392.8
506.1
458.4
387.4
426.9
565
464.8
444.5
449.5
556.1
499.6
451.9
434.9
553.8
510
432.9
453.2
547.6
485.8
452.6
456.6
565.7
514.8
464.3
430.9
588.3
503.1
442.6
448
554.5
504.5
427.3
473.1
526.2
547.5
440.2
468.7
574.5
492.6
432.6
479.8
575.7
474.6
405.3
434.6
535.1
452.6
429.5
417.2
551.8
464
416.6
422.9
553.6
458.6
427.6
429.2
534.2
481.7
416
440.2
538.7
473.8
439.9
446.8
597.5
467.2
439.4
447.4
568.5
485.9
442.1
430.5
600
464.5
423.6
437
574
443
410
420
532
432
420
411
512
449
382




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=34947&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=34947&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34947&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
mean392.087987012987408.267532467532426.51769480519524.939430420270134.4297077922078
median409.975427.45438.72529.165052402364328.7499999999999
midrange405.15406.44127.567479023790576.85000000000002

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 392.087987012987 & 408.267532467532 & 426.517694805195 & 24.9394304202701 & 34.4297077922078 \tabularnewline
median & 409.975 & 427.45 & 438.725 & 29.1650524023643 & 28.7499999999999 \tabularnewline
midrange & 405.15 & 406.4 & 412 & 7.56747902379057 & 6.85000000000002 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34947&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]392.087987012987[/C][C]408.267532467532[/C][C]426.517694805195[/C][C]24.9394304202701[/C][C]34.4297077922078[/C][/ROW]
[ROW][C]median[/C][C]409.975[/C][C]427.45[/C][C]438.725[/C][C]29.1650524023643[/C][C]28.7499999999999[/C][/ROW]
[ROW][C]midrange[/C][C]405.15[/C][C]406.4[/C][C]412[/C][C]7.56747902379057[/C][C]6.85000000000002[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34947&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34947&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
mean392.087987012987408.267532467532426.51769480519524.939430420270134.4297077922078
median409.975427.45438.72529.165052402364328.7499999999999
midrange405.15406.44127.567479023790576.85000000000002



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')