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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_variancereduction.wasp
Title produced by softwareVariance Reduction Matrix
Date of computationMon, 12 Dec 2011 07:45:00 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/12/t13236939214dv15ku8y9err4l.htm/, Retrieved Fri, 03 May 2024 11:00:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=153940, Retrieved Fri, 03 May 2024 11:00:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact108

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
F RMPD  [Univariate Explorative Data Analysis] [Colombia Coffee] [2008-01-07 14:21:11] [74be16979710d4c4e7c6647856088456]
- RMPD    [Univariate Explorative Data Analysis] [paper] [2011-11-24 11:53:20] [74be16979710d4c4e7c6647856088456]
- RMPD        [Variance Reduction Matrix] [paper] [2011-12-12 12:45:00] [7a9891c1925ad1e8ddfe52b8c5887b5b] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
374.92
375.63
376.51
377.75
378.54
378.21
376.65
374.28
373.12
373.1
374.67
375.97
377.03
377.87
378.88
380.42
380.62
379.66
377.48
376.07
374.1
374.47
376.15
377.51
378.43
379.7
380.91
382.2
382.45
382.14
380.6
378.6
376.72
376.98
378.29
380.07
381.36
382.19
382.65
384.65
384.94
384.01
382.15
380.33
378.81
379.06
380.17
381.85
382.88
383.77
384.42
386.36
386.53
386.01
384.45
381.96
380.81
381.09
382.37
383.84
385.42
385.72
385.96
387.18
388.5
387.88
386.38
384.15
383.07
382.98
384.11
385.54
386.92
387.41
388.77
389.46
390.18
389.43
387.74
385.91
384.77
384.38
385.99
387.26

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=153940&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]1 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=153940&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=153940&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 time1 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Variance Reduction Matrix
V(Y[t],d=0,D=0)19.0119746844521Range17.08Trim Var.13.3882759718623
V(Y[t],d=1,D=0)1.63121163679106Range4.49000000000001Trim Var.1.25809490106544
V(Y[t],d=2,D=0)0.971271303824147Range4.27999999999997Trim Var.0.636171654929576
V(Y[t],d=3,D=0)1.4136536111111Range6.14999999999992Trim Var.0.776304627766585
V(Y[t],d=0,D=1)1.63121163679106Range4.49000000000001Trim Var.1.25809490106544
V(Y[t],d=1,D=1)0.971271303824147Range4.27999999999997Trim Var.0.636171654929576
V(Y[t],d=2,D=1)1.4136536111111Range6.14999999999992Trim Var.0.776304627766585
V(Y[t],d=3,D=1)3.68967960443032Range9.38999999999987Trim Var.2.2099272104851
V(Y[t],d=0,D=2)0.971271303824147Range4.27999999999997Trim Var.0.636171654929576
V(Y[t],d=1,D=2)1.4136536111111Range6.14999999999992Trim Var.0.776304627766585
V(Y[t],d=2,D=2)3.68967960443032Range9.38999999999987Trim Var.2.2099272104851
V(Y[t],d=3,D=2)12.0802434274584Range17.0599999999998Trim Var.7.28438531187119

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 19.0119746844521 & Range & 17.08 & Trim Var. & 13.3882759718623 \tabularnewline
V(Y[t],d=1,D=0) & 1.63121163679106 & Range & 4.49000000000001 & Trim Var. & 1.25809490106544 \tabularnewline
V(Y[t],d=2,D=0) & 0.971271303824147 & Range & 4.27999999999997 & Trim Var. & 0.636171654929576 \tabularnewline
V(Y[t],d=3,D=0) & 1.4136536111111 & Range & 6.14999999999992 & Trim Var. & 0.776304627766585 \tabularnewline
V(Y[t],d=0,D=1) & 1.63121163679106 & Range & 4.49000000000001 & Trim Var. & 1.25809490106544 \tabularnewline
V(Y[t],d=1,D=1) & 0.971271303824147 & Range & 4.27999999999997 & Trim Var. & 0.636171654929576 \tabularnewline
V(Y[t],d=2,D=1) & 1.4136536111111 & Range & 6.14999999999992 & Trim Var. & 0.776304627766585 \tabularnewline
V(Y[t],d=3,D=1) & 3.68967960443032 & Range & 9.38999999999987 & Trim Var. & 2.2099272104851 \tabularnewline
V(Y[t],d=0,D=2) & 0.971271303824147 & Range & 4.27999999999997 & Trim Var. & 0.636171654929576 \tabularnewline
V(Y[t],d=1,D=2) & 1.4136536111111 & Range & 6.14999999999992 & Trim Var. & 0.776304627766585 \tabularnewline
V(Y[t],d=2,D=2) & 3.68967960443032 & Range & 9.38999999999987 & Trim Var. & 2.2099272104851 \tabularnewline
V(Y[t],d=3,D=2) & 12.0802434274584 & Range & 17.0599999999998 & Trim Var. & 7.28438531187119 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=153940&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]19.0119746844521[/C][C]Range[/C][C]17.08[/C][C]Trim Var.[/C][C]13.3882759718623[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]1.63121163679106[/C][C]Range[/C][C]4.49000000000001[/C][C]Trim Var.[/C][C]1.25809490106544[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]0.971271303824147[/C][C]Range[/C][C]4.27999999999997[/C][C]Trim Var.[/C][C]0.636171654929576[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]1.4136536111111[/C][C]Range[/C][C]6.14999999999992[/C][C]Trim Var.[/C][C]0.776304627766585[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]1.63121163679106[/C][C]Range[/C][C]4.49000000000001[/C][C]Trim Var.[/C][C]1.25809490106544[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.971271303824147[/C][C]Range[/C][C]4.27999999999997[/C][C]Trim Var.[/C][C]0.636171654929576[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]1.4136536111111[/C][C]Range[/C][C]6.14999999999992[/C][C]Trim Var.[/C][C]0.776304627766585[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]3.68967960443032[/C][C]Range[/C][C]9.38999999999987[/C][C]Trim Var.[/C][C]2.2099272104851[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]0.971271303824147[/C][C]Range[/C][C]4.27999999999997[/C][C]Trim Var.[/C][C]0.636171654929576[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]1.4136536111111[/C][C]Range[/C][C]6.14999999999992[/C][C]Trim Var.[/C][C]0.776304627766585[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]3.68967960443032[/C][C]Range[/C][C]9.38999999999987[/C][C]Trim Var.[/C][C]2.2099272104851[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]12.0802434274584[/C][C]Range[/C][C]17.0599999999998[/C][C]Trim Var.[/C][C]7.28438531187119[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=153940&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=153940&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:

Variance Reduction Matrix
V(Y[t],d=0,D=0)19.0119746844521Range17.08Trim Var.13.3882759718623
V(Y[t],d=1,D=0)1.63121163679106Range4.49000000000001Trim Var.1.25809490106544
V(Y[t],d=2,D=0)0.971271303824147Range4.27999999999997Trim Var.0.636171654929576
V(Y[t],d=3,D=0)1.4136536111111Range6.14999999999992Trim Var.0.776304627766585
V(Y[t],d=0,D=1)1.63121163679106Range4.49000000000001Trim Var.1.25809490106544
V(Y[t],d=1,D=1)0.971271303824147Range4.27999999999997Trim Var.0.636171654929576
V(Y[t],d=2,D=1)1.4136536111111Range6.14999999999992Trim Var.0.776304627766585
V(Y[t],d=3,D=1)3.68967960443032Range9.38999999999987Trim Var.2.2099272104851
V(Y[t],d=0,D=2)0.971271303824147Range4.27999999999997Trim Var.0.636171654929576
V(Y[t],d=1,D=2)1.4136536111111Range6.14999999999992Trim Var.0.776304627766585
V(Y[t],d=2,D=2)3.68967960443032Range9.38999999999987Trim Var.2.2099272104851
V(Y[t],d=3,D=2)12.0802434274584Range17.0599999999998Trim Var.7.28438531187119


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = additive ; par2 = 12 ;
Parameters (R input):
par1 = 1 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
n <- length(x)
sx <- sort(x)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Variance Reduction Matrix',6,TRUE)
a<-table.row.end(a)
for (bigd in 0:2) {
for (smalld in 0:3) {
mylabel <- 'V(Y[t],d='
mylabel <- paste(mylabel,as.character(smalld),sep='')
mylabel <- paste(mylabel,',D=',sep='')
mylabel <- paste(mylabel,as.character(bigd),sep='')
mylabel <- paste(mylabel,')',sep='')
a<-table.row.start(a)
a<-table.element(a,mylabel,header=TRUE)
myx <- x
if (smalld > 0) myx <- diff(myx,lag=1,differences=smalld)
if (bigd > 0) myx <- diff(myx,lag=par1,differences=bigd)
a<-table.element(a,var(myx))
a<-table.element(a,'Range',header=TRUE)
a<-table.element(a,max(myx)-min(myx))
a<-table.element(a,'Trim Var.',header=TRUE)
smyx <- sort(myx)
sn <- length(smyx)
a<-table.element(a,var(smyx[smyx>quantile(smyx,0.05) & smyxa<-table.row.end(a)
}
}
a<-table.end(a)
table.save(a,file='mytable.tab')
bitmap(file='pic0.png')
op <- par(mfrow=c(2,2))
plot(x,type='l',xlab='time',ylab='value',main='d=0, D=0')
plot(diff(x,lag=1,differences=1),type='l',xlab='time',ylab='value',main='d=1, D=0')
plot(diff(x,lag=par1,differences=1),type='l',xlab='time',ylab='value',main='d=0, D=1')
plot(diff(diff(x,lag=1,differences=1),lag=par1,differences=1),type='l',xlab='time',ylab='value',main='d=1, D=1')
par(op)
dev.off()