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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 computationTue, 16 Dec 2014 13:05:34 +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/2014/Dec/16/t14187351394aeo7gw4gaqw9nz.htm/, Retrieved Thu, 16 May 2024 23:10:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=269473, Retrieved Thu, 16 May 2024 23:10:18 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact82

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Blocked Bootstrap Plot - Central Tendency] [] [2014-12-16 13:05:34] [6f1b1943390e6908ad1cf28c6ee297e8] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2.25892
-1.29359
-0.920014
-5.5369
-3.9301
-3.03206
0.803242
0.144455
0.207334
-4.96333
-3.26506
-5.01001
0.713676
-1.38976
5.29186
-1.50333
-0.645347
-1.22947
-4.36062
-3.04073
-6.41111
2.66673
-3.72189
-1.4437
-0.493127
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0.82794
-0.98053
-2.83563
-2.34581
-3.02676
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-1.8382
0.967164
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-1.45618
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1.61385
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1.30797
1.19333
-1.26289
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3.41831
1.42682
2.44028
-1.71846
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0.485059
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0.225464
-2.01033
-3.68598
1.40941
0.741718
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5.1284
2.10324
1.66783
3.1531
4.49829
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3.50759
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1.10935
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2.60483
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3.55269
2.52618
2.89267
1.61434
1.64788
2.76053
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2.75102
6.05313
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0.496705
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1.0561
3.58036
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1.38904
2.70999
2.94255
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0.0560955
1.15785
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3.01846
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3.67328
2.80359
4.06244
0.922815
0.653328
-2.34056
2.04227
2.47903
-1.73993
3.43823
2.19866
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1.28365
3.37976
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0.69048
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3.43982
3.80722
2.97676
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0.64584
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3.47745
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1.61252
1.56356
-0.196845
4.08601
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0.496705
0.139499
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0.785233
2.61071
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3.9099
0.295437
2.33442
1.1429
2.81402
4.2603
-0.542289
1.6599
2.10754

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'Herman Ole Andreas Wold' @ wold.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269473&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269473&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269473&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'Herman Ole Andreas Wold' @ wold.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.






Estimation Results of Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean-0.28704273898917-1.16245487367391e-070.2004681754512640.3519612067771870.487510914440433
median-0.04453870.2361840.5844250.4432667074346090.6289637
midrange-0.751265-0.45082-0.4005150.2726094518361210.35075

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & -0.28704273898917 & -1.16245487367391e-07 & 0.200468175451264 & 0.351961206777187 & 0.487510914440433 \tabularnewline
median & -0.0445387 & 0.236184 & 0.584425 & 0.443266707434609 & 0.6289637 \tabularnewline
midrange & -0.751265 & -0.45082 & -0.400515 & 0.272609451836121 & 0.35075 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269473&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]-0.28704273898917[/C][C]-1.16245487367391e-07[/C][C]0.200468175451264[/C][C]0.351961206777187[/C][C]0.487510914440433[/C][/ROW]
[ROW][C]median[/C][C]-0.0445387[/C][C]0.236184[/C][C]0.584425[/C][C]0.443266707434609[/C][C]0.6289637[/C][/ROW]
[ROW][C]midrange[/C][C]-0.751265[/C][C]-0.45082[/C][C]-0.400515[/C][C]0.272609451836121[/C][C]0.35075[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269473&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269473&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-0.28704273898917-1.16245487367391e-070.2004681754512640.3519612067771870.487510914440433
median-0.04453870.2361840.5844250.4432667074346090.6289637
midrange-0.751265-0.45082-0.4005150.2726094518361210.35075


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 277 ; par2 = 12 ;
Parameters (R input):
par1 = 277 ; 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')