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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_bootstrapplot.wasp
Title produced by softwareBlocked Bootstrap Plot - Central Tendency
Date of computationThu, 25 Nov 2010 20:41:13 +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/Nov/25/t12907177577shu5eykmoc84fg.htm/, Retrieved Fri, 26 Apr 2024 16:13:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=101516, Retrieved Fri, 26 Apr 2024 16:13:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact117

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
- RMPD  [Blocked Bootstrap Plot - Central Tendency] [Colombia Coffee] [2008-01-07 10:26:26] [74be16979710d4c4e7c6647856088456]
- RM D      [Blocked Bootstrap Plot - Central Tendency] [Mini-Tutorial (Ce...] [2010-11-25 20:41:13] [6427096bd21c899f2c90594929aeeec2] [Current]
-    D        [Blocked Bootstrap Plot - Central Tendency] [Mini-Tutorial (Ce...] [2010-11-25 21:04:25] [845827b7f02503df17c96f445745fee7]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
-200,5
-256
-52,3
-29,1
200,6
788,5
629,1
-331,8
754,1
896,5
839,3
-284,9
516,8
264,8
426
679,4
396,9
676,4
154,2
-75,3
371,8
575,9
282,4
-1607,2
-199,4
-215,5
-608,5
-323,5
-225,9
-131,2
-204
-981,4
-285,7
-187,8
-806,4
-854,1
153,5
4,3
-135,5
-144,2
-269,1
-320,8
309,1
-323,4
-65,9
-270,6
-246
-1478,7
-777,6
-673
-17,4
-1094,6
-238,1
-504,2
-517,1
-498,8

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'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=101516&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=101516&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=101516&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Estimation Results of Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean-225.677678571429-116.355357142857-30.65625140.679684731188195.021428571429
median-220.7-193.6-105.4128.563549554250115.3
midrange-409.35-355.35-291.1110.485493714753118.25

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & -225.677678571429 & -116.355357142857 & -30.65625 & 140.679684731188 & 195.021428571429 \tabularnewline
median & -220.7 & -193.6 & -105.4 & 128.563549554250 & 115.3 \tabularnewline
midrange & -409.35 & -355.35 & -291.1 & 110.485493714753 & 118.25 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=101516&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]-225.677678571429[/C][C]-116.355357142857[/C][C]-30.65625[/C][C]140.679684731188[/C][C]195.021428571429[/C][/ROW]
[ROW][C]median[/C][C]-220.7[/C][C]-193.6[/C][C]-105.4[/C][C]128.563549554250[/C][C]115.3[/C][/ROW]
[ROW][C]midrange[/C][C]-409.35[/C][C]-355.35[/C][C]-291.1[/C][C]110.485493714753[/C][C]118.25[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=101516&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=101516&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
mean-225.677678571429-116.355357142857-30.65625140.679684731188195.021428571429
median-220.7-193.6-105.4128.563549554250115.3
midrange-409.35-355.35-291.1110.485493714753118.25


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 500 ; par2 = 12 ;
Parameters (R input):
par1 = 500 ; 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')