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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_bootstrapplot.wasp
Title produced by softwareBlocked Bootstrap Plot - Central Tendency
Date of computationTue, 06 Jan 2015 10:19:09 +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/2015/Jan/06/t14205396112znvrgxvs56jkpd.htm/, Retrieved Wed, 15 May 2024 10:30:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=271994, Retrieved Wed, 15 May 2024 10:30:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact147

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Harrell-Davis Quantiles] [] [2015-01-05 16:01:40] [a8f6a7eeade7f89f597831d453788737]
-    D  [Harrell-Davis Quantiles] [] [2015-01-05 16:10:43] [a8f6a7eeade7f89f597831d453788737]
- RM      [(Partial) Autocorrelation Function] [] [2015-01-06 09:12:41] [a8f6a7eeade7f89f597831d453788737]
- RM D      [Bootstrap Plot - Central Tendency] [] [2015-01-06 09:27:21] [a8f6a7eeade7f89f597831d453788737]
- RM D          [Blocked Bootstrap Plot - Central Tendency] [] [2015-01-06 10:19:09] [12470bd120139be5e23c611c04d9c0dc] [Current]
- RM D            [Variability] [] [2015-01-06 11:02:39] [a8f6a7eeade7f89f597831d453788737]
- RM D            [Standard Deviation Plot] [] [2015-01-06 11:07:17] [a8f6a7eeade7f89f597831d453788737]
- RM D            [Standard Deviation-Mean Plot] [] [2015-01-06 11:32:43] [a8f6a7eeade7f89f597831d453788737]
- RM              [Variability] [] [2015-01-06 11:43:50] [a8f6a7eeade7f89f597831d453788737]
- RM              [Standard Deviation Plot] [] [2015-01-06 11:48:58] [a8f6a7eeade7f89f597831d453788737]
- RM              [Standard Deviation-Mean Plot] [] [2015-01-06 12:01:28] [a8f6a7eeade7f89f597831d453788737]
- RM D            [Classical Decomposition] [] [2015-01-06 12:12:48] [a8f6a7eeade7f89f597831d453788737]
- RM                [Exponential Smoothing] [] [2015-01-06 12:25:54] [a8f6a7eeade7f89f597831d453788737]
- RM D              [Exponential Smoothing] [] [2015-01-06 12:34:40] [a8f6a7eeade7f89f597831d453788737]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
383
349
317
401
285
377
380
347
414
406
487
475
566
604
764
725
585
797
740
587
719
621
677
636
591
636
748
571
475
758
554
597
521
597
658
482
567
605
653
512
653
498
520
606
601
608
732
585
800
721
689
689
777
681
836
594
662
835
702
630
857
847
820
801
900
763
897
687
682
844
687
671

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=271994&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=271994&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=271994&T=0

As an alternative you can also use a QR Code:  
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'Gwilym Jenkins' @ jenkins.wessa.net






Estimation Results of Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean599.875625.583333333333638.04166666666733.575917651759338.1666666666666
median606633667.2534.103122425720461.25
midrange591592.5608.532.996519606201617.5

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 599.875 & 625.583333333333 & 638.041666666667 & 33.5759176517593 & 38.1666666666666 \tabularnewline
median & 606 & 633 & 667.25 & 34.1031224257204 & 61.25 \tabularnewline
midrange & 591 & 592.5 & 608.5 & 32.9965196062016 & 17.5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=271994&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]599.875[/C][C]625.583333333333[/C][C]638.041666666667[/C][C]33.5759176517593[/C][C]38.1666666666666[/C][/ROW]
[ROW][C]median[/C][C]606[/C][C]633[/C][C]667.25[/C][C]34.1031224257204[/C][C]61.25[/C][/ROW]
[ROW][C]midrange[/C][C]591[/C][C]592.5[/C][C]608.5[/C][C]32.9965196062016[/C][C]17.5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=271994&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=271994&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Estimation Results of Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean599.875625.583333333333638.04166666666733.575917651759338.1666666666666
median606633667.2534.103122425720461.25
midrange591592.5608.532.996519606201617.5


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0.1 ; par2 = 0.9 ; par3 = 0.1 ;
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')