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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 computationWed, 28 Nov 2012 09:25:52 -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/2012/Nov/28/t1354112771h1tl7d7gn90klcq.htm/, Retrieved Thu, 25 Apr 2024 17:16:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=194157, Retrieved Thu, 25 Apr 2024 17:16:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact79

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Variance Reduction Matrix] [paper deel 4; VRM...] [2012-11-28 14:25:52] [4e0a07d67ff6ab1ee99ce2372e43edac] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
369.07
369.32
370.38
371.63
371.32
371.51
369.69
368.18
366.87
366.94
368.27
369.62
370.47
371.44
372.39
373.32
373.77
373.13
371.51
369.59
368.12
368.38
369.64
371.11
372.38
373.08
373.87
374.93
375.58
375.44
373.91
371.77
370.72
370.5
372.19
373.71
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
388.45
389.7
391.08
392.46
392.96
392.03
390.13
388.15
386.8
387.18
388.59

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 2 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=194157&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=194157&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=194157&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 time2 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net






Variance Reduction Matrix
V(Y[t],d=0,D=0)44.8474835936582Range26.09Trim Var.33.8381523872679
V(Y[t],d=1,D=0)1.55939377459749Range4.49000000000001Trim Var.1.24912721889055
V(Y[t],d=2,D=0)0.893523195251935Range4.34999999999997Trim Var.0.588214691075514
V(Y[t],d=3,D=0)1.23001592027559Range6.14999999999992Trim Var.0.6830778217668
V(Y[t],d=0,D=1)0.237092522432701Range2.30000000000001Trim Var.0.161843243486073
V(Y[t],d=1,D=1)0.162545270172391Range1.98000000000002Trim Var.0.100110700808628
V(Y[t],d=2,D=1)0.400358325965229Range3.63999999999999Trim Var.0.210334853479856
V(Y[t],d=3,D=1)1.22190809595204Range6.31999999999994Trim Var.0.640690664675154
V(Y[t],d=0,D=2)0.650082260624228Range4.19999999999987Trim Var.0.419156595744687
V(Y[t],d=1,D=2)0.433174132973957Range3.28000000000009Trim Var.0.267279158087405
V(Y[t],d=2,D=2)1.02008062271066Range5.25999999999993Trim Var.0.610913183730746
V(Y[t],d=3,D=2)2.95607885548928Range9.10999999999984Trim Var.1.68538623984726

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 44.8474835936582 & Range & 26.09 & Trim Var. & 33.8381523872679 \tabularnewline
V(Y[t],d=1,D=0) & 1.55939377459749 & Range & 4.49000000000001 & Trim Var. & 1.24912721889055 \tabularnewline
V(Y[t],d=2,D=0) & 0.893523195251935 & Range & 4.34999999999997 & Trim Var. & 0.588214691075514 \tabularnewline
V(Y[t],d=3,D=0) & 1.23001592027559 & Range & 6.14999999999992 & Trim Var. & 0.6830778217668 \tabularnewline
V(Y[t],d=0,D=1) & 0.237092522432701 & Range & 2.30000000000001 & Trim Var. & 0.161843243486073 \tabularnewline
V(Y[t],d=1,D=1) & 0.162545270172391 & Range & 1.98000000000002 & Trim Var. & 0.100110700808628 \tabularnewline
V(Y[t],d=2,D=1) & 0.400358325965229 & Range & 3.63999999999999 & Trim Var. & 0.210334853479856 \tabularnewline
V(Y[t],d=3,D=1) & 1.22190809595204 & Range & 6.31999999999994 & Trim Var. & 0.640690664675154 \tabularnewline
V(Y[t],d=0,D=2) & 0.650082260624228 & Range & 4.19999999999987 & Trim Var. & 0.419156595744687 \tabularnewline
V(Y[t],d=1,D=2) & 0.433174132973957 & Range & 3.28000000000009 & Trim Var. & 0.267279158087405 \tabularnewline
V(Y[t],d=2,D=2) & 1.02008062271066 & Range & 5.25999999999993 & Trim Var. & 0.610913183730746 \tabularnewline
V(Y[t],d=3,D=2) & 2.95607885548928 & Range & 9.10999999999984 & Trim Var. & 1.68538623984726 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=194157&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]44.8474835936582[/C][C]Range[/C][C]26.09[/C][C]Trim Var.[/C][C]33.8381523872679[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]1.55939377459749[/C][C]Range[/C][C]4.49000000000001[/C][C]Trim Var.[/C][C]1.24912721889055[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]0.893523195251935[/C][C]Range[/C][C]4.34999999999997[/C][C]Trim Var.[/C][C]0.588214691075514[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]1.23001592027559[/C][C]Range[/C][C]6.14999999999992[/C][C]Trim Var.[/C][C]0.6830778217668[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]0.237092522432701[/C][C]Range[/C][C]2.30000000000001[/C][C]Trim Var.[/C][C]0.161843243486073[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.162545270172391[/C][C]Range[/C][C]1.98000000000002[/C][C]Trim Var.[/C][C]0.100110700808628[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]0.400358325965229[/C][C]Range[/C][C]3.63999999999999[/C][C]Trim Var.[/C][C]0.210334853479856[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]1.22190809595204[/C][C]Range[/C][C]6.31999999999994[/C][C]Trim Var.[/C][C]0.640690664675154[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]0.650082260624228[/C][C]Range[/C][C]4.19999999999987[/C][C]Trim Var.[/C][C]0.419156595744687[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]0.433174132973957[/C][C]Range[/C][C]3.28000000000009[/C][C]Trim Var.[/C][C]0.267279158087405[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]1.02008062271066[/C][C]Range[/C][C]5.25999999999993[/C][C]Trim Var.[/C][C]0.610913183730746[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]2.95607885548928[/C][C]Range[/C][C]9.10999999999984[/C][C]Trim Var.[/C][C]1.68538623984726[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=194157&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=194157&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)44.8474835936582Range26.09Trim Var.33.8381523872679
V(Y[t],d=1,D=0)1.55939377459749Range4.49000000000001Trim Var.1.24912721889055
V(Y[t],d=2,D=0)0.893523195251935Range4.34999999999997Trim Var.0.588214691075514
V(Y[t],d=3,D=0)1.23001592027559Range6.14999999999992Trim Var.0.6830778217668
V(Y[t],d=0,D=1)0.237092522432701Range2.30000000000001Trim Var.0.161843243486073
V(Y[t],d=1,D=1)0.162545270172391Range1.98000000000002Trim Var.0.100110700808628
V(Y[t],d=2,D=1)0.400358325965229Range3.63999999999999Trim Var.0.210334853479856
V(Y[t],d=3,D=1)1.22190809595204Range6.31999999999994Trim Var.0.640690664675154
V(Y[t],d=0,D=2)0.650082260624228Range4.19999999999987Trim Var.0.419156595744687
V(Y[t],d=1,D=2)0.433174132973957Range3.28000000000009Trim Var.0.267279158087405
V(Y[t],d=2,D=2)1.02008062271066Range5.25999999999993Trim Var.0.610913183730746
V(Y[t],d=3,D=2)2.95607885548928Range9.10999999999984Trim Var.1.68538623984726


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 12 ;
Parameters (R input):
par1 = 12 ;
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()