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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 computationThu, 29 Nov 2012 06:54:34 -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/29/t135419010631ws0o7jily7oq8.htm/, Retrieved Sat, 27 Apr 2024 20:28:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=194276, Retrieved Sat, 27 Apr 2024 20:28:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact109

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] [Workshop 9 - vari...] [2012-11-29 11:54:34] [3353489d44052879174bf0d9e8b7362f] [Current]
- RM D    [Standard Deviation-Mean Plot] [Workshop 9 - stan...] [2012-11-29 13:22:34] [9f87ad58f325f963ff5b3a15384d509e]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
8,64
8,89
8,87
8,81
8,87
9,06
9,12
8,66
8,17
8,04
7,71
7,55
7,52
7,38
7,52
7,31
6,92
7,09
7,05
7,37
7,05
6,79
6,35
6,44
6,89
7,16
7,46
7,91
7,86
8,02
8,38
8,50
8,40
8,24
8,33
8,28
8,15
8,06
7,79
7,28
7,52
7,23
7,13
7,21
6,99
6,77
6,69
6,39
6,85
6,74
6,56
6,62
6,71
6,67
6,54
6,14
6,13
5,86
5,88
5,75
5,53
5,86
5,90
5,95
5,69
5,53
5,71
5,60
5,73
5,60
5,41
5,13
5,00
5,04
5,10
4,96
4,90
4,80
4,48
4,29
4,27
4,18
4,02
3,82
4,13
4,16
3,98
4,26
4,70
4,96
5,13
5,35
5,41
5,42
5,51
5,75
5,67
5,46
5,56
5,56
5,54
5,53
5,65
5,58
5,57
5,36
5,23
5,11
5,07
5,04
5,34
5,43
5,31
5,12
4,97
5,00
4,64
4,80
5,10
5,11
5,12
5,36
5,26
5,27
5,10
4,94
4,68
4,41
4,60
4,53
4,18
4,00
3,87
4,09
4,13
3,74
3,81
4,11
4,14
3,99
4,28
4,37
4,24
4,19
4,01
3,95
4,30
4,37
4,40
4,29
4,12
4,07
3,93
3,79
3,67
3,53
3,69
3,69
3,48
3,31
3,16
3,25
3,14
3,19
3,43
3,45
3,31
3,51
3,53
3,83
4,02
3,99
4,11
3,96
3,83
3,71
3,81
3,73
3,99
4,17
4,00
4,10
4,24
4,45
4,62
4,49
4,45
4,49
4,36
4,32
4,45
4,13
4,14
4,30
4,42
4,67
4,96
4,73
4,52
 
 
 
 
4,36
4,15
3,92
3,88
4,20
3,95
3,78
3,69
 
 
 
 
3,77
3,66
3,53
3,50
3,14
3,42
3,30
2,81
3,15
3,37
4,05
4,00
4,20
4,21
4,24
4,24
4,17
4,12
4,35
3,98
3,62
4,39
5,01
4,07
3,70
3,59
3,44
3,33
2,98
3,14
2,55
2,49
2,53
2,43

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'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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=194276&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=194276&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=194276&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'Gwilym Jenkins' @ jenkins.wessa.net






Variance Reduction Matrix
V(Y[t],d=0,D=0)2.43533469917012Range6.69Trim Var.1.65217620951967
V(Y[t],d=1,D=0)0.0499766370292887Range1.71Trim Var.0.0274594957617909
V(Y[t],d=2,D=0)0.0874940649062972Range2.69Trim Var.0.0412657715764995
V(Y[t],d=3,D=0)0.241635565365387Range3.54Trim Var.0.123930691939801
V(Y[t],d=0,D=1)0.72938517582165Range4.05Trim Var.0.492088617886179
V(Y[t],d=1,D=1)0.0975326223046603Range1.81Trim Var.0.0571902902540326
V(Y[t],d=2,D=1)0.169020287708081Range2.52Trim Var.0.0926207823245378
V(Y[t],d=3,D=1)0.469478859390363Range4.15Trim Var.0.259707708979853
V(Y[t],d=0,D=2)1.95033979774706Range7.13Trim Var.1.2009823050489
V(Y[t],d=1,D=2)0.280850953919035Range3.15Trim Var.0.174509035307943
V(Y[t],d=2,D=2)0.470902229950011Range4.25Trim Var.0.268948510362694
V(Y[t],d=3,D=2)1.31460176385415Range6.84999999999999Trim Var.0.748345088896161

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 2.43533469917012 & Range & 6.69 & Trim Var. & 1.65217620951967 \tabularnewline
V(Y[t],d=1,D=0) & 0.0499766370292887 & Range & 1.71 & Trim Var. & 0.0274594957617909 \tabularnewline
V(Y[t],d=2,D=0) & 0.0874940649062972 & Range & 2.69 & Trim Var. & 0.0412657715764995 \tabularnewline
V(Y[t],d=3,D=0) & 0.241635565365387 & Range & 3.54 & Trim Var. & 0.123930691939801 \tabularnewline
V(Y[t],d=0,D=1) & 0.72938517582165 & Range & 4.05 & Trim Var. & 0.492088617886179 \tabularnewline
V(Y[t],d=1,D=1) & 0.0975326223046603 & Range & 1.81 & Trim Var. & 0.0571902902540326 \tabularnewline
V(Y[t],d=2,D=1) & 0.169020287708081 & Range & 2.52 & Trim Var. & 0.0926207823245378 \tabularnewline
V(Y[t],d=3,D=1) & 0.469478859390363 & Range & 4.15 & Trim Var. & 0.259707708979853 \tabularnewline
V(Y[t],d=0,D=2) & 1.95033979774706 & Range & 7.13 & Trim Var. & 1.2009823050489 \tabularnewline
V(Y[t],d=1,D=2) & 0.280850953919035 & Range & 3.15 & Trim Var. & 0.174509035307943 \tabularnewline
V(Y[t],d=2,D=2) & 0.470902229950011 & Range & 4.25 & Trim Var. & 0.268948510362694 \tabularnewline
V(Y[t],d=3,D=2) & 1.31460176385415 & Range & 6.84999999999999 & Trim Var. & 0.748345088896161 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=194276&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]2.43533469917012[/C][C]Range[/C][C]6.69[/C][C]Trim Var.[/C][C]1.65217620951967[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]0.0499766370292887[/C][C]Range[/C][C]1.71[/C][C]Trim Var.[/C][C]0.0274594957617909[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]0.0874940649062972[/C][C]Range[/C][C]2.69[/C][C]Trim Var.[/C][C]0.0412657715764995[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]0.241635565365387[/C][C]Range[/C][C]3.54[/C][C]Trim Var.[/C][C]0.123930691939801[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]0.72938517582165[/C][C]Range[/C][C]4.05[/C][C]Trim Var.[/C][C]0.492088617886179[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.0975326223046603[/C][C]Range[/C][C]1.81[/C][C]Trim Var.[/C][C]0.0571902902540326[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]0.169020287708081[/C][C]Range[/C][C]2.52[/C][C]Trim Var.[/C][C]0.0926207823245378[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]0.469478859390363[/C][C]Range[/C][C]4.15[/C][C]Trim Var.[/C][C]0.259707708979853[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]1.95033979774706[/C][C]Range[/C][C]7.13[/C][C]Trim Var.[/C][C]1.2009823050489[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]0.280850953919035[/C][C]Range[/C][C]3.15[/C][C]Trim Var.[/C][C]0.174509035307943[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]0.470902229950011[/C][C]Range[/C][C]4.25[/C][C]Trim Var.[/C][C]0.268948510362694[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]1.31460176385415[/C][C]Range[/C][C]6.84999999999999[/C][C]Trim Var.[/C][C]0.748345088896161[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=194276&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=194276&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)2.43533469917012Range6.69Trim Var.1.65217620951967
V(Y[t],d=1,D=0)0.0499766370292887Range1.71Trim Var.0.0274594957617909
V(Y[t],d=2,D=0)0.0874940649062972Range2.69Trim Var.0.0412657715764995
V(Y[t],d=3,D=0)0.241635565365387Range3.54Trim Var.0.123930691939801
V(Y[t],d=0,D=1)0.72938517582165Range4.05Trim Var.0.492088617886179
V(Y[t],d=1,D=1)0.0975326223046603Range1.81Trim Var.0.0571902902540326
V(Y[t],d=2,D=1)0.169020287708081Range2.52Trim Var.0.0926207823245378
V(Y[t],d=3,D=1)0.469478859390363Range4.15Trim Var.0.259707708979853
V(Y[t],d=0,D=2)1.95033979774706Range7.13Trim Var.1.2009823050489
V(Y[t],d=1,D=2)0.280850953919035Range3.15Trim Var.0.174509035307943
V(Y[t],d=2,D=2)0.470902229950011Range4.25Trim Var.0.268948510362694
V(Y[t],d=3,D=2)1.31460176385415Range6.84999999999999Trim Var.0.748345088896161


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()