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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_bootstrapplot.wasp
Title produced by softwareBlocked Bootstrap Plot - Central Tendency
Date of computationSun, 14 Dec 2008 10:29:20 -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/2008/Dec/14/t1229275809jc5bxjm5y21kax0.htm/, Retrieved Wed, 15 May 2024 23:56:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=33496, Retrieved Wed, 15 May 2024 23:56:51 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact210
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Industriele produ...] [2008-12-14 16:49:51] [b82ef11dce0545f3fd4676ec3ebed828]
- RMP   [Central Tendency] [Central Tendency ...] [2008-12-14 17:03:16] [b82ef11dce0545f3fd4676ec3ebed828]
- RM      [Percentiles] [Percentiles - - ...] [2008-12-14 17:08:17] [b82ef11dce0545f3fd4676ec3ebed828]
- RM        [Tukey lambda PPCC Plot] [Tukey lambda PPCC...] [2008-12-14 17:26:43] [b82ef11dce0545f3fd4676ec3ebed828]
- RMP           [Blocked Bootstrap Plot - Central Tendency] [Blocked bootstrap...] [2008-12-14 17:29:20] [4b953869c7238aca4b6e0cfb0c5cddd6] [Current]
- RMP             [Harrell-Davis Quantiles] [Harrell-Davis Qua...] [2008-12-14 17:35:42] [b82ef11dce0545f3fd4676ec3ebed828]
- RMP               [Univariate Explorative Data Analysis] [Univariate EDA -...] [2008-12-14 17:39:39] [b82ef11dce0545f3fd4676ec3ebed828]
- RMP                 [Mean Plot] [Mean plot - Indus...] [2008-12-14 17:56:47] [b82ef11dce0545f3fd4676ec3ebed828]
- RM                    [Variance Reduction Matrix] [VRM - Industriele...] [2008-12-14 18:03:27] [b82ef11dce0545f3fd4676ec3ebed828]
- RM                      [Standard Deviation-Mean Plot] [SDMP - Industriel...] [2008-12-14 18:07:34] [b82ef11dce0545f3fd4676ec3ebed828]
- RM                        [(Partial) Autocorrelation Function] [(Partial) ACF - ...] [2008-12-14 18:14:08] [b82ef11dce0545f3fd4676ec3ebed828]
- RM                          [Spectral Analysis] [Spectrum - Indust...] [2008-12-14 18:16:42] [b82ef11dce0545f3fd4676ec3ebed828]
- RM                            [ARIMA Backward Selection] [ARIMA Backward Se...] [2008-12-14 18:25:02] [b82ef11dce0545f3fd4676ec3ebed828]
- RM                              [ARIMA Forecasting] [ARIMA Forecasting...] [2008-12-14 18:33:23] [b82ef11dce0545f3fd4676ec3ebed828]
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Dataseries X:
97.4
97
105.4
102.7
98.1
104.5
87.4
89.9
109.8
111.7
98.6
96.9
95.1
97
112.7
102.9
97.4
111.4
87.4
96.8
114.1
110.3
103.9
101.6
94.6
95.9
104.7
102.8
98.1
113.9
80.9
95.7
113.2
105.9
108.8
102.3
99
100.7
115.5
100.7
109.9
114.6
85.4
100.5
114.8
116.5
112.9
102
106
105.3
118.8
106.1
109.3
117.2
92.5
104.2
112.5
122.4
113.3
100
110.7
112.8
109.8
117.3
109.1
115.9
96
99.8
117




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33496&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33496&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33496&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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Estimation Results of Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean103.630434782609104.569565217391105.6695652173911.459938175191022.03913043478261
median102.9104.5105.92.051104634201013
midrange101.35101.65103.11.689254673726081.75

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 103.630434782609 & 104.569565217391 & 105.669565217391 & 1.45993817519102 & 2.03913043478261 \tabularnewline
median & 102.9 & 104.5 & 105.9 & 2.05110463420101 & 3 \tabularnewline
midrange & 101.35 & 101.65 & 103.1 & 1.68925467372608 & 1.75 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33496&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]103.630434782609[/C][C]104.569565217391[/C][C]105.669565217391[/C][C]1.45993817519102[/C][C]2.03913043478261[/C][/ROW]
[ROW][C]median[/C][C]102.9[/C][C]104.5[/C][C]105.9[/C][C]2.05110463420101[/C][C]3[/C][/ROW]
[ROW][C]midrange[/C][C]101.35[/C][C]101.65[/C][C]103.1[/C][C]1.68925467372608[/C][C]1.75[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33496&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33496&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
mean103.630434782609104.569565217391105.6695652173911.459938175191022.03913043478261
median102.9104.5105.92.051104634201013
midrange101.35101.65103.11.689254673726081.75



Parameters (Session):
par1 = 500 ; par2 = 12 ;
Parameters (R input):
par1 = 500 ; 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')