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Author

*The author of this computation has been verified*

R Software Module

rwasp_bootstrapplot1.wasp

Title produced by software

Bootstrap Plot - Central Tendency

Date of computation

Tue, 16 Dec 2014 09:39:51 +0000

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/16/t1418722952hyj2ko11jsdcspo.htm/, Retrieved Thu, 16 May 2024 04:48:28 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=269211, Retrieved Thu, 16 May 2024 04:48:28 +0000

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Estimated Impact

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Bootstrap Plot - Central Tendency] [] [2014-12-16 09:39:51] [00948489e79095d843a5e7d0a51f3696] [Current]

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Dataseries X:

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Histogram

Boxplots

-1,29552
-6,41697
-1,61397
-1,432
-6,30415
-7,18061
-2,50838
1,33138
-0,185791
-2,39986
-7,42168
-2,67362
-7,5121
-1,66185
-2,01918
-4,68132
-0,477008
-2,01089
-3,64904
-4,19613
-2,1094
-7,00176
-0,260993
-4,36442
-0,402389
-2,31204
-4,11383
1,6823
0,842372
-3,99359
-1,39474
-3,23674
-2,41574
-6,99811
-4,25033
-4,01933
-1,71821
-2,51649
-2,45004
-0,413312
-5,5793
-1,74536
-7,63817
-2,749
-1,06748
-2,51022
1,15666
-3,65444
-0,979399
-4,37096
0,774192
-0,210468
-0,970903
-4,3685
-2,8245
-1,498
-0,0403176
-2,9682
-6,79938
1,28564
-2,62465
0,300274
-5,38461
-1,48788
-4,19714
0,891956
-5,60067
-2,71173
-3,14672
-2,43686
0,0875358
-0,24235
-2,83652
-1,73362
-3,59933
1,07464
-6,85434
0,450215
-0,548117
-0,537537
-0,853124
-1,18345
-4,97802
-1,98526
1,38977
-1,00532
-7,86149
-2,51183
-1,2259
-0,833874
-0,137417
-3,85482
0,470952
0,488184
-6,95483
-3,5232
-3,42125
-4,95551
-3,8284
-6,24852
-1,14494
1,08723
-4,66607
-1,00529
-1,77136
-2,65774
-3,21353
1,8842
-3,72081
1,24278
-6,66835
-4,8953
-2,97454
-1,21016
-1,39683
-7,94904
1,24221
4,52786
3,93632
2,78777
0,457843
1,3429
4,65396
1,86028
1,7369
3,94764
3,88628
-1,98633
0,252967
2,95037
0,886392
5,23545
1,1226
1,13831
2,00667
2,32906
2,29742
0,622541
0,110985
4,10634
-2,00977
4,83695
2,22021
-0,451989
4,02805
2,53262
4,99623
2,13408
2,6064
3,2582
-0,22163
-1,62235
1,52565
1,94623
3,32681
-3,35521
2,52814
3,80448
2,69972
2,19382
1,11372
3,81633
2,88411
0,926709
-0,000846216
5,02158
3,84178
2,63474
5,30497
4,41108
-0,557277
5,39836
2,44693
1,93001
-0,805945
3,12845
5,0224
0,724264
0,632938
0,749219
5,3486
-0,132022
5,66036
1,69896
-3,45418
0,495473
0,761351
5,17267
3,09294
-0,548312
2,7708
4,2205
0,0936131
-1,17853
1,46968
-1,67149
3,65109
-2,44933
5,67622
1,41517
1,33821
1,20204
2,61317
3,03466
3,13758
1,00981
0,778034
0,390412
3,15852
0,50974
3,09872
-0,844599
0,317464
0,486873
7,69656
4,66444
-0,18824
1,61265
0,0102794
2,07927
2,8454
-0,374375
3,41705
0,105157
3,91895
-0,270727
2,27793
4,90667
-2,76196
-1,29698
3,09531
5,57596
3,53736
3,7908
3,30151
5,64045
5,59128
5,13472
5,4585
1,28149
-0,81367
-1,83786
-7,41442
0,866838
0,48938
-0,676063
0,514872
0,389144
1,06188
2,12067
5,04962
4,08731
-1,7065
2,24683
3,52175
0,850088
2,95909
0,157149
-1,52637
0,137609
2,35835
3,51591
-1,07826
3,65263
-3,49834
-4,049
0,39459
-5,00293
-1,57423
0,22129
-2,63825
2,04925
4,28113
1,18677
1,47136
3,78654
3,45938
-0,5734
2,97713
0,634013
4,05617
4,82513
2,44126
0,992056
3,84166
-2,91006

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	6 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 & 6 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269211&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]6 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=269211&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269211&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	6 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

Estimation Results of Bootstrap
statistic	P1	P5	Q1	Estimate	Q3	P95	P99	S.D.	IQR
mean	-0.3824	-0.31091	-0.15006	-1.7663e-07	0.10356	0.26093	0.42588	0.18173	0.25362
median	-0.25181	-0.1616	0.097849	0.27662	0.39302	0.49971	0.62949	0.21055	0.29517
midrange	-1.1545	-1.1443	-1.0926	-0.12624	-0.082465	0.029195	0.09223	0.47699	1.0102
mode	-7.1829	-4.5939	-1.7162	-1.7663e-07	1.2149	3.6606	5.6762	2.5849	2.9311
mode k.dens	-0.97715	-0.34027	0.29555	0.4602	0.749	1.1097	2.6108	0.55227	0.45345

\begin{tabular}{lllllllll}
\hline
Estimation Results of Bootstrap \tabularnewline
statistic & P1 & P5 & Q1 & Estimate & Q3 & P95 & P99 & S.D. & IQR \tabularnewline
mean & -0.3824 & -0.31091 & -0.15006 & -1.7663e-07 & 0.10356 & 0.26093 & 0.42588 & 0.18173 & 0.25362 \tabularnewline
median & -0.25181 & -0.1616 & 0.097849 & 0.27662 & 0.39302 & 0.49971 & 0.62949 & 0.21055 & 0.29517 \tabularnewline
midrange & -1.1545 & -1.1443 & -1.0926 & -0.12624 & -0.082465 & 0.029195 & 0.09223 & 0.47699 & 1.0102 \tabularnewline
mode & -7.1829 & -4.5939 & -1.7162 & -1.7663e-07 & 1.2149 & 3.6606 & 5.6762 & 2.5849 & 2.9311 \tabularnewline
mode k.dens & -0.97715 & -0.34027 & 0.29555 & 0.4602 & 0.749 & 1.1097 & 2.6108 & 0.55227 & 0.45345 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269211&T=1

[TABLE]
[ROW][C]Estimation Results of Bootstrap[/C][/ROW]
[ROW][C]statistic[/C][C]P1[/C][C]P5[/C][C]Q1[/C][C]Estimate[/C][C]Q3[/C][C]P95[/C][C]P99[/C][C]S.D.[/C][C]IQR[/C][/ROW]
[ROW][C]mean[/C][C]-0.3824[/C][C]-0.31091[/C][C]-0.15006[/C][C]-1.7663e-07[/C][C]0.10356[/C][C]0.26093[/C][C]0.42588[/C][C]0.18173[/C][C]0.25362[/C][/ROW]
[ROW][C]median[/C][C]-0.25181[/C][C]-0.1616[/C][C]0.097849[/C][C]0.27662[/C][C]0.39302[/C][C]0.49971[/C][C]0.62949[/C][C]0.21055[/C][C]0.29517[/C][/ROW]
[ROW][C]midrange[/C][C]-1.1545[/C][C]-1.1443[/C][C]-1.0926[/C][C]-0.12624[/C][C]-0.082465[/C][C]0.029195[/C][C]0.09223[/C][C]0.47699[/C][C]1.0102[/C][/ROW]
[ROW][C]mode[/C][C]-7.1829[/C][C]-4.5939[/C][C]-1.7162[/C][C]-1.7663e-07[/C][C]1.2149[/C][C]3.6606[/C][C]5.6762[/C][C]2.5849[/C][C]2.9311[/C][/ROW]
[ROW][C]mode k.dens[/C][C]-0.97715[/C][C]-0.34027[/C][C]0.29555[/C][C]0.4602[/C][C]0.749[/C][C]1.1097[/C][C]2.6108[/C][C]0.55227[/C][C]0.45345[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269211&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269211&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 Bootstrap
statistic	P1	P5	Q1	Estimate	Q3	P95	P99	S.D.	IQR
mean	-0.3824	-0.31091	-0.15006	-1.7663e-07	0.10356	0.26093	0.42588	0.18173	0.25362
median	-0.25181	-0.1616	0.097849	0.27662	0.39302	0.49971	0.62949	0.21055	0.29517
midrange	-1.1545	-1.1443	-1.0926	-0.12624	-0.082465	0.029195	0.09223	0.47699	1.0102
mode	-7.1829	-4.5939	-1.7162	-1.7663e-07	1.2149	3.6606	5.6762	2.5849	2.9311
mode k.dens	-0.97715	-0.34027	0.29555	0.4602	0.749	1.1097	2.6108	0.55227	0.45345

Figure 1

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Figure 2

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Figure 3

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Figure 4

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Figure 5

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Figure 6

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Figure 7

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Figure 8

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Figure 9

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Figure 10

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Figure 11

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Parameters (Session):

par1 = 200 ; par2 = 5 ; par3 = 0 ; par4 = P1 P5 Q1 Q3 P95 P99 ;

Parameters (R input):

par1 = 200 ; par2 = 5 ; par3 = 0 ; par4 = P1 P5 Q1 Q3 P95 P99 ;

R code (references can be found in the software module):

par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
if (par3 == '0') bw <- NULL
if (par3 != '0') bw <- as.numeric(par3)
if (par1 < 10) par1 = 10
if (par1 > 5000) par1 = 5000
library(modeest)
library(lattice)
library(boot)
boot.stat <- function(s,i)
{
s.mean <- mean(s[i])
s.median <- median(s[i])
s.midrange <- (max(s[i]) + min(s[i])) / 2
s.mode <- mlv(s[i], method='mfv')$M
s.kernelmode <- mlv(s[i], method='kernel', bw=bw)$M
c(s.mean, s.median, s.midrange, s.mode, s.kernelmode)
}
(r <- boot(x,boot.stat, R=par1, stype='i'))
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$t[,3],type='p',ylab='simulated values',main='Simulation of Midrange')
grid()
dev.off()
bitmap(file='plot7.png')
plot(r$t[,4],type='p',ylab='simulated values',main='Simulation of Mode')
grid()
dev.off()
bitmap(file='plot8.png')
plot(r$t[,5],type='p',ylab='simulated values',main='Simulation of Mode of Kernel Density')
grid()
dev.off()
bitmap(file='plot4.png')
densityplot(~r$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()
bitmap(file='plot9.png')
densityplot(~r$t[,4],col='black',main='Density Plot',xlab='mode')
dev.off()
bitmap(file='plot10.png')
densityplot(~r$t[,5],col='black',main='Density Plot',xlab='mode of kernel dens.')
dev.off()
z <- data.frame(cbind(r$t[,1],r$t[,2],r$t[,3],r$t[,4],r$t[,5]))
colnames(z) <- list('mean','median','midrange','mode','mode k.dens')
bitmap(file='plot11.png')
boxplot(z,notch=TRUE,ylab='simulated values',main='Bootstrap Simulation - Central Tendency')
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Estimation Results of Bootstrap',10,TRUE)
a<-table.row.end(a)
if (par4 == 'P1 P5 Q1 Q3 P95 P99') {
myq.1 <- 0.01
myq.2 <- 0.05
myq.3 <- 0.95
myq.4 <- 0.99
myl.1 <- 'P1'
myl.2 <- 'P5'
myl.3 <- 'P95'
myl.4 <- 'P99'
}
if (par4 == 'P0.5 P2.5 Q1 Q3 P97.5 P99.5') {
myq.1 <- 0.005
myq.2 <- 0.025
myq.3 <- 0.975
myq.4 <- 0.995
myl.1 <- 'P0.5'
myl.2 <- 'P2.5'
myl.3 <- 'P97.5'
myl.4 <- 'P99.5'
}
if (par4 == 'P10 P20 Q1 Q3 P80 P90') {
myq.1 <- 0.10
myq.2 <- 0.20
myq.3 <- 0.80
myq.4 <- 0.90
myl.1 <- 'P10'
myl.2 <- 'P20'
myl.3 <- 'P80'
myl.4 <- 'P90'
}
a<-table.row.start(a)
a<-table.element(a,'statistic',header=TRUE)
a<-table.element(a,myl.1,header=TRUE)
a<-table.element(a,myl.2,header=TRUE)
a<-table.element(a,'Q1',header=TRUE)
a<-table.element(a,'Estimate',header=TRUE)
a<-table.element(a,'Q3',header=TRUE)
a<-table.element(a,myl.3,header=TRUE)
a<-table.element(a,myl.4,header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'IQR',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
q1 <- quantile(r$t[,1],0.25)[[1]]
q3 <- quantile(r$t[,1],0.75)[[1]]
p01 <- quantile(r$t[,1],myq.1)[[1]]
p05 <- quantile(r$t[,1],myq.2)[[1]]
p95 <- quantile(r$t[,1],myq.3)[[1]]
p99 <- quantile(r$t[,1],myq.4)[[1]]
a<-table.element(a,signif(p01,par2))
a<-table.element(a,signif(p05,par2))
a<-table.element(a,signif(q1,par2))
a<-table.element(a,signif(r$t0[1],par2))
a<-table.element(a,signif(q3,par2))
a<-table.element(a,signif(p95,par2))
a<-table.element(a,signif(p99,par2))
a<-table.element( a,signif( sqrt(var(r$t[,1])),par2 ) )
a<-table.element(a,signif(q3-q1,par2))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'median',header=TRUE)
q1 <- quantile(r$t[,2],0.25)[[1]]
q3 <- quantile(r$t[,2],0.75)[[1]]
p01 <- quantile(r$t[,2],myq.1)[[1]]
p05 <- quantile(r$t[,2],myq.2)[[1]]
p95 <- quantile(r$t[,2],myq.3)[[1]]
p99 <- quantile(r$t[,2],myq.4)[[1]]
a<-table.element(a,signif(p01,par2))
a<-table.element(a,signif(p05,par2))
a<-table.element(a,signif(q1,par2))
a<-table.element(a,signif(r$t0[2],par2))
a<-table.element(a,signif(q3,par2))
a<-table.element(a,signif(p95,par2))
a<-table.element(a,signif(p99,par2))
a<-table.element(a,signif(sqrt(var(r$t[,2])),par2))
a<-table.element(a,signif(q3-q1,par2))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'midrange',header=TRUE)
q1 <- quantile(r$t[,3],0.25)[[1]]
q3 <- quantile(r$t[,3],0.75)[[1]]
p01 <- quantile(r$t[,3],myq.1)[[1]]
p05 <- quantile(r$t[,3],myq.2)[[1]]
p95 <- quantile(r$t[,3],myq.3)[[1]]
p99 <- quantile(r$t[,3],myq.4)[[1]]
a<-table.element(a,signif(p01,par2))
a<-table.element(a,signif(p05,par2))
a<-table.element(a,signif(q1,par2))
a<-table.element(a,signif(r$t0[3],par2))
a<-table.element(a,signif(q3,par2))
a<-table.element(a,signif(p95,par2))
a<-table.element(a,signif(p99,par2))
a<-table.element(a,signif(sqrt(var(r$t[,3])),par2))
a<-table.element(a,signif(q3-q1,par2))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mode',header=TRUE)
q1 <- quantile(r$t[,4],0.25)[[1]]
q3 <- quantile(r$t[,4],0.75)[[1]]
p01 <- quantile(r$t[,4],myq.1)[[1]]
p05 <- quantile(r$t[,4],myq.2)[[1]]
p95 <- quantile(r$t[,4],myq.3)[[1]]
p99 <- quantile(r$t[,4],myq.4)[[1]]
a<-table.element(a,signif(p01,par2))
a<-table.element(a,signif(p05,par2))
a<-table.element(a,signif(q1,par2))
a<-table.element(a,signif(r$t0[4],par2))
a<-table.element(a,signif(q3,par2))
a<-table.element(a,signif(p95,par2))
a<-table.element(a,signif(p99,par2))
a<-table.element(a,signif(sqrt(var(r$t[,4])),par2))
a<-table.element(a,signif(q3-q1,par2))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mode k.dens',header=TRUE)
q1 <- quantile(r$t[,5],0.25)[[1]]
q3 <- quantile(r$t[,5],0.75)[[1]]
p01 <- quantile(r$t[,5],myq.1)[[1]]
p05 <- quantile(r$t[,5],myq.2)[[1]]
p95 <- quantile(r$t[,5],myq.3)[[1]]
p99 <- quantile(r$t[,5],myq.4)[[1]]
a<-table.element(a,signif(p01,par2))
a<-table.element(a,signif(p05,par2))
a<-table.element(a,signif(q1,par2))
a<-table.element(a,signif(r$t0[5],par2))
a<-table.element(a,signif(q3,par2))
a<-table.element(a,signif(p95,par2))
a<-table.element(a,signif(p99,par2))
a<-table.element(a,signif(sqrt(var(r$t[,5])),par2))
a<-table.element(a,signif(q3-q1,par2))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code