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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, 22 Oct 2013 10:40:12 -0400

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/2013/Oct/22/t1382452827akrsbrd73xjts0s.htm/, Retrieved Sun, 28 Apr 2024 21:59:44 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=218532, Retrieved Sun, 28 Apr 2024 21:59:44 +0000

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-     [Notched Boxplots] [Academic Motivati...] [2010-10-12 12:51:42] [b98453cac15ba1066b407e146608df68]
- RMP     [Bootstrap Plot - Central Tendency] [Q7, deel 2] [2013-10-22 14:40:12] [39bbe84484d657d2e6fd8a60bf77f148] [Current]

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26	21	21	23	17	23	4
20	16	15	24	17	20	4
19	19	18	22	18	20	6
19	18	11	20	21	21	8
20	16	8	24	20	24	8
25	23	19	27	28	22	4
25	17	4	28	19	23	4
22	12	20	27	22	20	8
26	19	16	24	16	25	5
22	16	14	23	18	23	4
17	19	10	24	25	27	4
22	20	13	27	17	27	4
19	13	14	27	14	22	4
24	20	8	28	11	24	4
26	27	23	27	27	25	4
21	17	11	23	20	22	8
13	8	9	24	22	28	4
26	25	24	28	22	28	4
20	26	5	27	21	27	4
22	13	15	25	23	25	8
14	19	5	19	17	16	4
21	15	19	24	24	28	7
7	5	6	20	14	21	4
23	16	13	28	17	24	4
17	14	11	26	23	27	5
25	24	17	23	24	14	4
25	24	17	23	24	14	4
19	9	5	20	8	27	4
20	19	9	11	22	20	4
23	19	15	24	23	21	4
22	25	17	25	25	22	4
22	19	17	23	21	21	4
21	18	20	18	24	12	15
15	15	12	20	15	20	10
20	12	7	20	22	24	4
22	21	16	24	21	19	8
18	12	7	23	25	28	4
20	15	14	25	16	23	4
28	28	24	28	28	27	4
22	25	15	26	23	22	4
18	19	15	26	21	27	7
23	20	10	23	21	26	4
20	24	14	22	26	22	6
25	26	18	24	22	21	5
26	25	12	21	21	19	4
15	12	9	20	18	24	16
17	12	9	22	12	19	5
23	15	8	20	25	26	12
21	17	18	25	17	22	6
13	14	10	20	24	28	9
18	16	17	22	15	21	9
19	11	14	23	13	23	4
22	20	16	25	26	28	5
16	11	10	23	16	10	4
24	22	19	23	24	24	4
18	20	10	22	21	21	5
20	19	14	24	20	21	4
24	17	10	25	14	24	4
14	21	4	21	25	24	4
22	23	19	12	25	25	5
24	18	9	17	20	25	4
18	17	12	20	22	23	6
21	27	16	23	20	21	4
23	25	11	23	26	16	4
17	19	18	20	18	17	18
22	22	11	28	22	25	4
24	24	24	24	24	24	6
21	20	17	24	17	23	4
22	19	18	24	24	25	4
16	11	9	24	20	23	5
21	22	19	28	19	28	4
23	22	18	25	20	26	4
22	16	12	21	15	22	5
24	20	23	25	23	19	10
24	24	22	25	26	26	5
16	16	14	18	22	18	8
16	16	14	17	20	18	8
21	22	16	26	24	25	5
26	24	23	28	26	27	4
15	16	7	21	21	12	4
25	27	10	27	25	15	4
18	11	12	22	13	21	5
23	21	12	21	20	23	4
20	20	12	25	22	22	4
17	20	17	22	23	21	8
25	27	21	23	28	24	4
24	20	16	26	22	27	5
17	12	11	19	20	22	14
19	8	14	25	6	28	8
20	21	13	21	21	26	8
15	18	9	13	20	10	4
27	24	19	24	18	19	4
22	16	13	25	23	22	6
23	18	19	26	20	21	4
16	20	13	25	24	24	7
19	20	13	25	22	25	7
25	19	13	22	21	21	4
19	17	14	21	18	20	6
19	16	12	23	21	21	4
26	26	22	25	23	24	7
21	15	11	24	23	23	4
20	22	5	21	15	18	4
24	17	18	21	21	24	8
22	23	19	25	24	24	4
20	21	14	22	23	19	4
18	19	15	20	21	20	10
18	14	12	20	21	18	8
24	17	19	23	20	20	6
24	12	15	28	11	27	4
22	24	17	23	22	23	4
23	18	8	28	27	26	4
22	20	10	24	25	23	5
20	16	12	18	18	17	4
18	20	12	20	20	21	6
25	22	20	28	24	25	4
18	12	12	21	10	23	5
16	16	12	21	27	27	7
20	17	14	25	21	24	8
19	22	6	19	21	20	5
15	12	10	18	18	27	8
19	14	18	21	15	21	10
19	23	18	22	24	24	8
16	15	7	24	22	21	5
17	17	18	15	14	15	12
28	28	9	28	28	25	4
23	20	17	26	18	25	5
25	23	22	23	26	22	4
20	13	11	26	17	24	6
17	18	15	20	19	21	4
23	23	17	22	22	22	4
16	19	15	20	18	23	7
23	23	22	23	24	22	7
11	12	9	22	15	20	10
18	16	13	24	18	23	4
24	23	20	23	26	25	5
23	13	14	22	11	23	8
21	22	14	26	26	22	11
16	18	12	23	21	25	7
24	23	20	27	23	26	4
23	20	20	23	23	22	8
18	10	8	21	15	24	6
20	17	17	26	22	24	7
9	18	9	23	26	25	5
24	15	18	21	16	20	4
25	23	22	27	20	26	8
20	17	10	19	18	21	4
21	17	13	23	22	26	8
25	22	15	25	16	21	6
22	20	18	23	19	22	4
21	20	18	22	20	16	9
21	19	12	22	19	26	5
22	18	12	25	23	28	6
27	22	20	25	24	18	4
24	20	12	28	25	25	4
24	22	16	28	21	23	4
21	18	16	20	21	21	5
18	16	18	25	23	20	6
16	16	16	19	27	25	16
22	16	13	25	23	22	6
20	16	17	22	18	21	6
18	17	13	18	16	16	4
20	18	17	20	16	18	4

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=218532&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]2 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=218532&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=218532&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	2 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

Parameters (Session):

par1 = grey ;

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')

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Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code