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R Software Module

rwasp_bootstrapplot1.wasp

Title produced by software

Bootstrap Plot - Central Tendency

Date of computation

Sat, 25 May 2013 12:48:52 -0400

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/May/25/t1369500652xzj9xnndde8ovp7.htm/, Retrieved Thu, 02 May 2024 18:39:43 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=210531, Retrieved Thu, 02 May 2024 18:39:43 +0000

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

-       [Bootstrap Plot - Central Tendency] [] [2013-05-25 16:48:52] [f2eb9e6f8a572d38d7977956fe5c285e] [Current]

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	19 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 & 19 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=210531&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]19 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=210531&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=210531&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	19 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

Estimation Results of Bootstrap
statistic	P1	P5	Q1	Estimate	Q3	P95	P99	S.D.	IQR
mean	70.437	70.555	70.748	70.871	71.01	71.183	71.296	0.18861	0.26208
median	70.4	70.637	70.864	71.11	71.16	71.238	71.4	0.22026	0.29625
midrange	70.45	70.83	71.015	71.02	71.19	71.24	71.39	0.14802	0.175
mode	68.4	68.98	70.114	70.89	71.436	72.56	73.08	1.1023	1.3221
mode k.dens	70.457	70.704	71.054	71.183	71.31	71.492	71.631	0.29556	0.25566

\begin{tabular}{lllllllll}
\hline
Estimation Results of Bootstrap \tabularnewline
statistic & P1 & P5 & Q1 & Estimate & Q3 & P95 & P99 & S.D. & IQR \tabularnewline
mean & 70.437 & 70.555 & 70.748 & 70.871 & 71.01 & 71.183 & 71.296 & 0.18861 & 0.26208 \tabularnewline
median & 70.4 & 70.637 & 70.864 & 71.11 & 71.16 & 71.238 & 71.4 & 0.22026 & 0.29625 \tabularnewline
midrange & 70.45 & 70.83 & 71.015 & 71.02 & 71.19 & 71.24 & 71.39 & 0.14802 & 0.175 \tabularnewline
mode & 68.4 & 68.98 & 70.114 & 70.89 & 71.436 & 72.56 & 73.08 & 1.1023 & 1.3221 \tabularnewline
mode k.dens & 70.457 & 70.704 & 71.054 & 71.183 & 71.31 & 71.492 & 71.631 & 0.29556 & 0.25566 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=210531&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]70.437[/C][C]70.555[/C][C]70.748[/C][C]70.871[/C][C]71.01[/C][C]71.183[/C][C]71.296[/C][C]0.18861[/C][C]0.26208[/C][/ROW]
[ROW][C]median[/C][C]70.4[/C][C]70.637[/C][C]70.864[/C][C]71.11[/C][C]71.16[/C][C]71.238[/C][C]71.4[/C][C]0.22026[/C][C]0.29625[/C][/ROW]
[ROW][C]midrange[/C][C]70.45[/C][C]70.83[/C][C]71.015[/C][C]71.02[/C][C]71.19[/C][C]71.24[/C][C]71.39[/C][C]0.14802[/C][C]0.175[/C][/ROW]
[ROW][C]mode[/C][C]68.4[/C][C]68.98[/C][C]70.114[/C][C]70.89[/C][C]71.436[/C][C]72.56[/C][C]73.08[/C][C]1.1023[/C][C]1.3221[/C][/ROW]
[ROW][C]mode k.dens[/C][C]70.457[/C][C]70.704[/C][C]71.054[/C][C]71.183[/C][C]71.31[/C][C]71.492[/C][C]71.631[/C][C]0.29556[/C][C]0.25566[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=210531&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=210531&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	70.437	70.555	70.748	70.871	71.01	71.183	71.296	0.18861	0.26208
median	70.4	70.637	70.864	71.11	71.16	71.238	71.4	0.22026	0.29625
midrange	70.45	70.83	71.015	71.02	71.19	71.24	71.39	0.14802	0.175
mode	68.4	68.98	70.114	70.89	71.436	72.56	73.08	1.1023	1.3221
mode k.dens	70.457	70.704	71.054	71.183	71.31	71.492	71.631	0.29556	0.25566

Figure 1

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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 = 750 ; par2 = 5 ; par3 = 0 ;

Parameters (R input):

par1 = 750 ; par2 = 5 ; par3 = 0 ;

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

par3 <- '0'
par2 <- '5'
par1 <- '200'
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$t[,5]))
colnames(z) <- list('mean','median','midrange','mode','mode k.dens')
bitmap(file='plot11.png')
boxplot(z,notch=TRUE,ylab='simulated values',main='Bootstrap Simulation - Central Tendency')
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Estimation Results of Bootstrap',10,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'statistic',header=TRUE)
a<-table.element(a,'P1',header=TRUE)
a<-table.element(a,'P5',header=TRUE)
a<-table.element(a,'Q1',header=TRUE)
a<-table.element(a,'Estimate',header=TRUE)
a<-table.element(a,'Q3',header=TRUE)
a<-table.element(a,'P95',header=TRUE)
a<-table.element(a,'P99',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'IQR',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
q1 <- quantile(r$t[,1],0.25)[[1]]
q3 <- quantile(r$t[,1],0.75)[[1]]
p01 <- quantile(r$t[,1],0.01)[[1]]
p05 <- quantile(r$t[,1],0.05)[[1]]
p95 <- quantile(r$t[,1],0.95)[[1]]
p99 <- quantile(r$t[,1],0.99)[[1]]
a<-table.element(a,signif(p01,par2))
a<-table.element(a,signif(p05,par2))
a<-table.element(a,signif(q1,par2))
a<-table.element(a,signif(r$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],0.01)[[1]]
p05 <- quantile(r$t[,2],0.05)[[1]]
p95 <- quantile(r$t[,2],0.95)[[1]]
p99 <- quantile(r$t[,2],0.99)[[1]]
a<-table.element(a,signif(p01,par2))
a<-table.element(a,signif(p05,par2))
a<-table.element(a,signif(q1,par2))
a<-table.element(a,signif(r$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],0.01)[[1]]
p05 <- quantile(r$t[,3],0.05)[[1]]
p95 <- quantile(r$t[,3],0.95)[[1]]
p99 <- quantile(r$t[,3],0.99)[[1]]
a<-table.element(a,signif(p01,par2))
a<-table.element(a,signif(p05,par2))
a<-table.element(a,signif(q1,par2))
a<-table.element(a,signif(r$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],0.01)[[1]]
p05 <- quantile(r$t[,4],0.05)[[1]]
p95 <- quantile(r$t[,4],0.95)[[1]]
p99 <- quantile(r$t[,4],0.99)[[1]]
a<-table.element(a,signif(p01,par2))
a<-table.element(a,signif(p05,par2))
a<-table.element(a,signif(q1,par2))
a<-table.element(a,signif(r$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],0.01)[[1]]
p05 <- quantile(r$t[,5],0.05)[[1]]
p95 <- quantile(r$t[,5],0.95)[[1]]
p99 <- quantile(r$t[,5],0.99)[[1]]
a<-table.element(a,signif(p01,par2))
a<-table.element(a,signif(p05,par2))
a<-table.element(a,signif(q1,par2))
a<-table.element(a,signif(r$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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Input Parameters & R Code