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Author's title

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

Wed, 02 Sep 2015 21:03:36 +0100

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/2015/Sep/02/t1441224332xyun7kx39yh5gw6.htm/, Retrieved Wed, 15 May 2024 21:36:25 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=280413, Retrieved Wed, 15 May 2024 21:36:25 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

137

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

-     [Multiple Regression] [] [2010-11-17 09:14:55] [b98453cac15ba1066b407e146608df68]
- RMPD    [Bootstrap Plot - Central Tendency] [] [2015-09-02 20:03:36] [3e99441ea7f7f69c8fa4628f6be951c3] [Current]

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Dataseries X:

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Histogram

Boxplots

-7.347
-3.834
0.6011
10.17
-19.38
76.99
5.531
-40.66
7.892
17.29
12.68
19.65
-22.86
24.21
-102.8
-22.15
19.52
-27.51
32.82
-23.62
9.836
4.607
70.54
50.22
-0.6102
109.5
38.38
-17.13
9.891
8.935
-50.61
6.248
-15.46
17.4
-39.24
-41.63
5.69
31.4
20.6
4.546
-32.83
5.298
18.88
21.04
-34.81
32.33
-31.54
-6.965
-51.19
-19.62
16.33
-54.32
11.08
51.42
-17.44
-28.83
23.01
-6.313
-53.84
-12.25
13.19
8.396
-42.78
59.81
36.25
-29.86
38.38
76.01
45.97
-1.176
21.41
-26.72
-36.28
-1.786
-12.25
2.563
1.161
9.311
-27.95
-35.91
-16.47
7.289
-19.36
1.193
22.25
0.5881
-19.15
-32.84
-19.92
28.56
-27.29
20.32
39.28
-9.731
-0.9424
9.605
18.17
-4.938
-7.562
12.84
-30.49
-3.639
-17.9
30.41
-5.727
-9.332
-5.541
-14.8
-55.83
-7.45
7.463
3.415
-77.99
-70.92
25.01
29.24
10.27
-13.37
60.45
27.8
28.78
-65.83
18.46
-89.5
-19.62
-11.25
9.828
-20.78
40.67
-28.59
-10.68
26.04
-9.826
-7.377
-50.72
-40.82
-1.701
-99.8
14.14
-11.37
-11.59
43.86
32.06
1.175
15.59
5.307
0.3095
-25.62
0.8553
45.83
34.61
-22.3
25.73
38.26
-20.42
5.136
36.92
-22.44
17.9
-14.71
20.7
4.385
35.85
-125
64.32
-31.38
22.98
9.225
7.163
-6.14
10.53
19.03
40.87
38.67
38.67
29
-6.404
23.14
56.32
-81.46
-6.584
26.08
19.86
5.209
57.02
9.457
7.457
12.46
16.31
-34.72
-27.97
33.49
-10.28
22.25
-13.11
-18.45
9.357
3.318
-9.621
18.73
89.78
-23.68
13.01
21.74
-3.676
-28.96
-76.99
-32.69
49.38
17.34
-49.69
25.46
-21.83
-12.78
14.66
-21.79
9.074
48.88
-33.94
10.8
13.23
-33.88
-23.43
7.381
39.52
-41.81
9.44
1.736
-11.37
14.41
36.79
11.44
3.583
42.25
-29.78
-79.35
-47.25
22
-55.94
-1.495
-25.02
-28.11
15.24
64.32
-1.896
29.79
31.4
-13.81
-7.755
10.66
12.04
-54.92
5.606
-11.45
36.12
14.2
-21.52
-47.59
11.8
25.01
-31.38
-9.648
7.745
15.24
8.141
-17.66
-23.86
22.11
24.43
-35.26
25.44
-11.14
9.017
12.61
19.19
-22.17
21.19
-67.41

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	'Sir Ronald Aylmer Fisher' @ fisher.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 & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280413&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]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=280413&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280413&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	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

Estimation Results of Bootstrap
statistic	P1	P5	Q1	Estimate	Q3	P95	P99	S.D.	IQR
mean	-4.9824	-3.8829	-1.3368	-0.00011727	1.2624	3.0493	4.3907	2.1085	2.5992
median	-2.7686	0.29347	1.736	4.4655	5.3136	7.3734	8.1533	2.5197	3.5776
midrange	-24.495	-24.005	-12.905	-7.75	3.35	4.85	10	9.1176	16.255
mode	-78.105	-42.877	-11.37	14.605	17.094	39.304	64.32	26.713	28.464
mode k.dens	-17.781	4.5746	8.8886	10.485	11.785	15.276	17.052	5.0747	2.8959

\begin{tabular}{lllllllll}
\hline
Estimation Results of Bootstrap \tabularnewline
statistic & P1 & P5 & Q1 & Estimate & Q3 & P95 & P99 & S.D. & IQR \tabularnewline
mean & -4.9824 & -3.8829 & -1.3368 & -0.00011727 & 1.2624 & 3.0493 & 4.3907 & 2.1085 & 2.5992 \tabularnewline
median & -2.7686 & 0.29347 & 1.736 & 4.4655 & 5.3136 & 7.3734 & 8.1533 & 2.5197 & 3.5776 \tabularnewline
midrange & -24.495 & -24.005 & -12.905 & -7.75 & 3.35 & 4.85 & 10 & 9.1176 & 16.255 \tabularnewline
mode & -78.105 & -42.877 & -11.37 & 14.605 & 17.094 & 39.304 & 64.32 & 26.713 & 28.464 \tabularnewline
mode k.dens & -17.781 & 4.5746 & 8.8886 & 10.485 & 11.785 & 15.276 & 17.052 & 5.0747 & 2.8959 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280413&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]-4.9824[/C][C]-3.8829[/C][C]-1.3368[/C][C]-0.00011727[/C][C]1.2624[/C][C]3.0493[/C][C]4.3907[/C][C]2.1085[/C][C]2.5992[/C][/ROW]
[ROW][C]median[/C][C]-2.7686[/C][C]0.29347[/C][C]1.736[/C][C]4.4655[/C][C]5.3136[/C][C]7.3734[/C][C]8.1533[/C][C]2.5197[/C][C]3.5776[/C][/ROW]
[ROW][C]midrange[/C][C]-24.495[/C][C]-24.005[/C][C]-12.905[/C][C]-7.75[/C][C]3.35[/C][C]4.85[/C][C]10[/C][C]9.1176[/C][C]16.255[/C][/ROW]
[ROW][C]mode[/C][C]-78.105[/C][C]-42.877[/C][C]-11.37[/C][C]14.605[/C][C]17.094[/C][C]39.304[/C][C]64.32[/C][C]26.713[/C][C]28.464[/C][/ROW]
[ROW][C]mode k.dens[/C][C]-17.781[/C][C]4.5746[/C][C]8.8886[/C][C]10.485[/C][C]11.785[/C][C]15.276[/C][C]17.052[/C][C]5.0747[/C][C]2.8959[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=280413&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280413&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	-4.9824	-3.8829	-1.3368	-0.00011727	1.2624	3.0493	4.3907	2.1085	2.5992
median	-2.7686	0.29347	1.736	4.4655	5.3136	7.3734	8.1533	2.5197	3.5776
midrange	-24.495	-24.005	-12.905	-7.75	3.35	4.85	10	9.1176	16.255
mode	-78.105	-42.877	-11.37	14.605	17.094	39.304	64.32	26.713	28.464
mode k.dens	-17.781	4.5746	8.8886	10.485	11.785	15.276	17.052	5.0747	2.8959

Figure 1

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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 = 0.95 ; par2 = 0 ;

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