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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 computationFri, 26 Nov 2010 14:36:57 +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/26/t1290782150umkutwock24j10c.htm/, Retrieved Sat, 04 May 2024 08:30:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=101938, Retrieved Sat, 04 May 2024 08:30:16 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact109

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] [] [2010-11-26 14:36:57] [c8b0d20ebafa6d61ca10522fa626ae82] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
14.267
472.071
12.335
16.434
10.132
37.190
27.169
21.389
17.416
9.862
8.326
17.578
26.242
20.290
8.089
24.421
9.155
18.061
14.693
8.034
19.516
33.256
17.737
8.886
12.187
18.837
12.341
21.003
18.421
14.225
10.730
14.558
20.347
16.235
39.199
33.492
79.503
21.210
15.907
16.399
7.887
19.976
23.664
12.518
2.385
20.643
16.756
8.932
36.014
10.815
26.268
8.534
14.107
19.193
9.594
18.053
15.805
9.578
8.321
33.400
11.547
12.677
14.138
10.545
10.982
40.070
7.399
10.250
23.433
15.080
29.558
23.587
2.093
39.654
8.285
8.931
34.526
35.350
6.566
10.244
11.090
8.969
12.206
17.525
12.953
18.466
15.110
12.575
24.394
4.401
31.119
11.201
14.781
38.557
29.500
21.700
10.934
4.893
13.080
4.721
18.021
14.916
13.534
8.747
12.229
28.129
9.647
5.915
9.435
9.280
11.673
7.538
23.025
5.837
13.894
19.563
6.356
9.460
9.300
12.637
7.587
18.662
15.058
92.704
13.784
10.937
15.290
20.969
32.207
14.050
8.048
7.049
22.317
10.219
5.246
14.806
18.450
117.073
10.875
13.675
22.111
19.755
22.060
2.768
34.026
15.998
9.307
8.342
12.019
3.346
34.812
997
19.837
17.775
12.092
8.167
7.792
3.672
14.116
9.597
11.283
26.328
73.941
12.649
5.467
32.450
35.963
30.930
23.898
2.050
15.578
11.384
13.574
18.378
69.175
8.955
12.243
9.928
10.620
26.781
9.371
8.489
10.840
56.547
11.040
8.223
11.031
7.502
6.586
5.128
19.474
9.093
13.461
9.086
4.963
10.285
21.515
11.062
11.748
78.271
17.937
31.667
17.528
16.999
17.473
36.219
9.534
24.660
19.201
14.452
13.973
43.618
23.547
11.851
17.651
10.312
23.414
11.063
20.457
13.637
19.825
6.171
22.397
6.592
12.242
19.028
28.799
10.251
17.451
32.545
12.226
237.250
7.999
20.734
9.418
10.710
22.705
5.942
11.080
11.431
13.241
8.251
7.776
7.026
8.033
14.713
8.148
29.050
24.639
6.953
13.881
6.382
6.135
2.073
6.475
6.446
7.919
45.887
15.489
38.489
18.387
70.450
17.096
27.285
7.605
41.984
18.001
64.294
7.966
8.812
71.543
11.958
14.636
14.007
6.707
9.807
38.828
17.228
20.306
6.985
9.974
31.278
12.561
14.774
12.118
32.424
24.139
16.247
13.719
15.996
13.898
11.612
29.993
12.664
19.296
11.153
30.384
10.339
6.898
84
9.412
8.151
24.935
16.145
29.859
7.102
36.661
4.207

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 5 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=101938&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=101938&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=101938&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 time5 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk






Estimation Results of Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean20.843180194805223.511425324675325.63029788961043.30609141489264.78711769480519
median13.69713.9914.4520.6784514837500210.755000000000001
midrange237.0605499.525499.525156.589005892367262.4645

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 20.8431801948052 & 23.5114253246753 & 25.6302978896104 & 3.3060914148926 & 4.78711769480519 \tabularnewline
median & 13.697 & 13.99 & 14.452 & 0.678451483750021 & 0.755000000000001 \tabularnewline
midrange & 237.0605 & 499.525 & 499.525 & 156.589005892367 & 262.4645 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=101938&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]20.8431801948052[/C][C]23.5114253246753[/C][C]25.6302978896104[/C][C]3.3060914148926[/C][C]4.78711769480519[/C][/ROW]
[ROW][C]median[/C][C]13.697[/C][C]13.99[/C][C]14.452[/C][C]0.678451483750021[/C][C]0.755000000000001[/C][/ROW]
[ROW][C]midrange[/C][C]237.0605[/C][C]499.525[/C][C]499.525[/C][C]156.589005892367[/C][C]262.4645[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=101938&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=101938&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
mean20.843180194805223.511425324675325.63029788961043.30609141489264.78711769480519
median13.69713.9914.4520.6784514837500210.755000000000001
midrange237.0605499.525499.525156.589005892367262.4645


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')