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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_bootstrapplot.wasp
Title produced by softwareBlocked Bootstrap Plot - Central Tendency
Date of computationSun, 04 Jan 2009 09:07:05 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Jan/04/t1231085307djni8dw21gyh44z.htm/, Retrieved Tue, 07 May 2024 11:51:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=36752, Retrieved Tue, 07 May 2024 11:51:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact244

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Harrell-Davis Quantiles] [Harrel davis deci...] [2008-10-18 16:19:32] [ea79f99c5895b39ae8bb6e8c563d0f54]
-   PD  [Harrell-Davis Quantiles] [Harrel davis deci...] [2008-10-18 17:17:36] [ea79f99c5895b39ae8bb6e8c563d0f54]
- RMPD    [(Partial) Autocorrelation Function] [OEF 2 deel 1 De L...] [2008-12-11 08:24:21] [ea79f99c5895b39ae8bb6e8c563d0f54]
- RMP       [Bootstrap Plot - Central Tendency] [Oef 2 opg. 7 De L...] [2008-12-18 22:45:41] [ea79f99c5895b39ae8bb6e8c563d0f54]
- RMP           [Blocked Bootstrap Plot - Central Tendency] [VERbetering Block...] [2009-01-04 16:07:05] [1eda150a0abaa7374d7583f55f7b1e6e] [Current]
- RMP             [Variability] [SDL OPG 8 OEF3 va...] [2009-01-06 10:22:38] [ea79f99c5895b39ae8bb6e8c563d0f54]
- RMP               [Classical Decomposition] [SDL OPG 9 OEF2] [2009-01-15 22:26:39] [74be16979710d4c4e7c6647856088456]
- RMP                 [Exponential Smoothing] [SDL OPG 10 OEF2] [2009-01-17 11:19:26] [74be16979710d4c4e7c6647856088456]
- RMP             [Standard Deviation Plot] [SDL OPG 8 OEF3 st...] [2009-01-06 10:27:14] [ea79f99c5895b39ae8bb6e8c563d0f54]
- RMP             [Standard Deviation-Mean Plot] [SDL OPG 8 OEF3 st...] [2009-01-06 10:33:01] [ea79f99c5895b39ae8bb6e8c563d0f54]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
102.9
102.9
102.9
102.9
104.2
104.7
104.7
104.7
104.7
104.7
104.7
104.7
104.7
104.7
104.7
104.7
106
107
107
107
107
107
107
107
107
107
107
107
107.6
109.9
109.9
109.9
109.9
109.9
109.9
109.9
109.9
109.9
109.9
109.9
110.6
114.3
114.3
114.3
114.3
114.3
114.3
114.3
114.3
114.3
114.3
114.3
114.3
119.01
119.01
119.01
119.01
119.01
119.01
119.01
119.01
119.01
119.01
119.01
121.27
123.54
123.54
123.54
123.54
123.54
123.54
123.54
123.54
123.54
123.54
123.54
123.54
125.24
125.24
125.24
125.24
125.24
125.24
125.24
125.24
125.24
125.24
125.24
125.24
128.35
128.35
128.35
128.35
128.35
128.35
128.35

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 3 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36752&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36752&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36752&T=0

As an alternative you can also use a QR Code:  
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 time3 seconds
R Server'George Udny Yule' @ 72.249.76.132






Estimation Results of Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean114.260208333333115.243645833333117.10656252.00825297193642.84635416666666
median114.3114.3119.014.294088941409424.71000000000001
midrange115.625115.625115.6250.6337969561560340

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 114.260208333333 & 115.243645833333 & 117.1065625 & 2.0082529719364 & 2.84635416666666 \tabularnewline
median & 114.3 & 114.3 & 119.01 & 4.29408894140942 & 4.71000000000001 \tabularnewline
midrange & 115.625 & 115.625 & 115.625 & 0.633796956156034 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36752&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]114.260208333333[/C][C]115.243645833333[/C][C]117.1065625[/C][C]2.0082529719364[/C][C]2.84635416666666[/C][/ROW]
[ROW][C]median[/C][C]114.3[/C][C]114.3[/C][C]119.01[/C][C]4.29408894140942[/C][C]4.71000000000001[/C][/ROW]
[ROW][C]midrange[/C][C]115.625[/C][C]115.625[/C][C]115.625[/C][C]0.633796956156034[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36752&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36752&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Estimation Results of Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean114.260208333333115.243645833333117.10656252.00825297193642.84635416666666
median114.3114.3119.014.294088941409424.71000000000001
midrange115.625115.625115.6250.6337969561560340


Figures (Output of Computation)

Input Parameters & R Code

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')