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Author's title

Blocked bootstrap plot - Buitenlandse handel van België - Marilyn Vandeputt...

Author*Unverified author*
R Software Modulerwasp_bootstrapplot.wasp
Title produced by softwareBlocked Bootstrap Plot - Central Tendency
Date of computationFri, 12 Apr 2013 08:16:07 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Apr/12/t1365769101qv5dszc07m4k0tq.htm/, Retrieved Sat, 04 May 2024 07:08:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=208020, Retrieved Sat, 04 May 2024 07:08:22 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact171
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Harrell-Davis Quantiles] [] [2013-02-27 17:18:27] [0a0b9be5aba9ab40348e88c5d8957fc2]
- R PD  [Harrell-Davis Quantiles] [Deciel Buitenland...] [2013-03-03 16:38:13] [0a0b9be5aba9ab40348e88c5d8957fc2]
- RMPD    [Bootstrap Plot - Central Tendency] [Bootsrap plot max...] [2013-04-12 11:59:16] [0a0b9be5aba9ab40348e88c5d8957fc2]
- RMPD        [Blocked Bootstrap Plot - Central Tendency] [Blocked bootstrap...] [2013-04-12 12:16:07] [aebd7ed62a520371cf0fbdf4b97f0dea] [Current]
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Dataseries X:
122,27
124,69
147,56
120,03
136,01
138,16
122,87
112,22
137,35
139,08
139,64
121,12
132,37
130,69
149,41
130,72
139,14
146,55
137,35
122,73
138,97
154,73
143,4
123,88
140,25
142,39
143,81
153,58
144,71
153,84
151,3
121,92
153,05
149,29
118,81
109,19
103,68
106,94
114,43
107,87
103,14
117,02
112,44
95,85
123,86
121,83
121,95
120,34
113,32
117,31
141,69
130,35
127,28
148,1
131,21
120,37
146,91
144,04
141,77
132,15
142,04
149,77
172,31
150,24
163,23
155,92
146,96
134,51
152,83
150,54
150,98
138,82




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'George Udny Yule' @ yule.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 & 5 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=208020&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=208020&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=208020&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'George Udny Yule' @ yule.wessa.net







Estimation Results of Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean129.355520833333133.959444444444136.7857291666674.441615540793837.43020833333333
median130.69137.35138.9656.397531083893838.27499999999998
midrange130.52375134.08134.084.894700607883623.55624999999998

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 129.355520833333 & 133.959444444444 & 136.785729166667 & 4.44161554079383 & 7.43020833333333 \tabularnewline
median & 130.69 & 137.35 & 138.965 & 6.39753108389383 & 8.27499999999998 \tabularnewline
midrange & 130.52375 & 134.08 & 134.08 & 4.89470060788362 & 3.55624999999998 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=208020&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]129.355520833333[/C][C]133.959444444444[/C][C]136.785729166667[/C][C]4.44161554079383[/C][C]7.43020833333333[/C][/ROW]
[ROW][C]median[/C][C]130.69[/C][C]137.35[/C][C]138.965[/C][C]6.39753108389383[/C][C]8.27499999999998[/C][/ROW]
[ROW][C]midrange[/C][C]130.52375[/C][C]134.08[/C][C]134.08[/C][C]4.89470060788362[/C][C]3.55624999999998[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=208020&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=208020&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 Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean129.355520833333133.959444444444136.7857291666674.441615540793837.43020833333333
median130.69137.35138.9656.397531083893838.27499999999998
midrange130.52375134.08134.084.894700607883623.55624999999998



Parameters (Session):
par1 = 50 ; par2 = 12 ;
Parameters (R input):
par1 = 50 ; 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')