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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 computationFri, 27 Nov 2009 02:02:37 -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/Nov/27/t12593131770weerma6sicps1m.htm/, Retrieved Mon, 29 Apr 2024 02:32:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60490, Retrieved Mon, 29 Apr 2024 02:32:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact192

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Variance Reduction Matrix] [Identifying Integ...] [2009-11-22 12:29:54] [b98453cac15ba1066b407e146608df68]
-    D          [Variance Reduction Matrix] [workshop 8] [2009-11-27 09:02:37] [a18540c86166a2b66550d1fef0503cc2] [Current]
-    D            [Variance Reduction Matrix] [WS9] [2009-12-06 13:33:02] [9f35ad889e41dd0c9322ca60d75b9f47]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
8,6
8,5
8,3
7,8
7,8
8
8,6
8,9
8,9
8,6
8,3
8,3
8,3
8,4
8,5
8,4
8,6
8,5
8,5
8,4
8,5
8,5
8,5
8,5
8,5
8,5
8,5
8,5
8,6
8,4
8,1
8
8
8
8
7,9
7,8
7,8
7,9
8,1
8
7,6
7,3
7
6,8
7
7,1
7,2
7,1
6,9
6,7
6,7
6,6
6,9
7,3
7,5
7,3
7,1
6,9
7,1

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' @ 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60490&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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60490&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60490&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' @ 72.249.127.135






Variance Reduction Matrix
V(Y[t],d=0,D=0)0.429771186440678Range2.3Trim Var.0.333342857142857
V(Y[t],d=1,D=0)0.0388252483927528Range1.1Trim Var.0.0189960784313725
V(Y[t],d=2,D=0)0.0422534785238959Range0.900000000000001Trim Var.0.0267918367346938
V(Y[t],d=3,D=0)0.0829573934837092Range1.5Trim Var.0.0481019607843137
V(Y[t],d=0,D=1)0.283364361702128Range2.2Trim Var.0.138677462887989
V(Y[t],d=1,D=1)0.0708510638297872Range1.3Trim Var.0.0336951219512195
V(Y[t],d=2,D=1)0.0615507246376812Range1.20000000000000Trim Var.0.0309679487179487
V(Y[t],d=3,D=1)0.093818181818182Range1.20000000000001Trim Var.0.0627260458839405
V(Y[t],d=0,D=2)0.458182539682540Range2.7Trim Var.0.269637096774193
V(Y[t],d=1,D=2)0.120285714285714Range1.50000000000000Trim Var.0.0753978494623654
V(Y[t],d=2,D=2)0.104206773618539Range1.50000000000000Trim Var.0.0547241379310346
V(Y[t],d=3,D=2)0.182348484848486Range1.90000000000001Trim Var.0.101699507389162

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 0.429771186440678 & Range & 2.3 & Trim Var. & 0.333342857142857 \tabularnewline
V(Y[t],d=1,D=0) & 0.0388252483927528 & Range & 1.1 & Trim Var. & 0.0189960784313725 \tabularnewline
V(Y[t],d=2,D=0) & 0.0422534785238959 & Range & 0.900000000000001 & Trim Var. & 0.0267918367346938 \tabularnewline
V(Y[t],d=3,D=0) & 0.0829573934837092 & Range & 1.5 & Trim Var. & 0.0481019607843137 \tabularnewline
V(Y[t],d=0,D=1) & 0.283364361702128 & Range & 2.2 & Trim Var. & 0.138677462887989 \tabularnewline
V(Y[t],d=1,D=1) & 0.0708510638297872 & Range & 1.3 & Trim Var. & 0.0336951219512195 \tabularnewline
V(Y[t],d=2,D=1) & 0.0615507246376812 & Range & 1.20000000000000 & Trim Var. & 0.0309679487179487 \tabularnewline
V(Y[t],d=3,D=1) & 0.093818181818182 & Range & 1.20000000000001 & Trim Var. & 0.0627260458839405 \tabularnewline
V(Y[t],d=0,D=2) & 0.458182539682540 & Range & 2.7 & Trim Var. & 0.269637096774193 \tabularnewline
V(Y[t],d=1,D=2) & 0.120285714285714 & Range & 1.50000000000000 & Trim Var. & 0.0753978494623654 \tabularnewline
V(Y[t],d=2,D=2) & 0.104206773618539 & Range & 1.50000000000000 & Trim Var. & 0.0547241379310346 \tabularnewline
V(Y[t],d=3,D=2) & 0.182348484848486 & Range & 1.90000000000001 & Trim Var. & 0.101699507389162 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60490&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]0.429771186440678[/C][C]Range[/C][C]2.3[/C][C]Trim Var.[/C][C]0.333342857142857[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]0.0388252483927528[/C][C]Range[/C][C]1.1[/C][C]Trim Var.[/C][C]0.0189960784313725[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]0.0422534785238959[/C][C]Range[/C][C]0.900000000000001[/C][C]Trim Var.[/C][C]0.0267918367346938[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]0.0829573934837092[/C][C]Range[/C][C]1.5[/C][C]Trim Var.[/C][C]0.0481019607843137[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]0.283364361702128[/C][C]Range[/C][C]2.2[/C][C]Trim Var.[/C][C]0.138677462887989[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.0708510638297872[/C][C]Range[/C][C]1.3[/C][C]Trim Var.[/C][C]0.0336951219512195[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]0.0615507246376812[/C][C]Range[/C][C]1.20000000000000[/C][C]Trim Var.[/C][C]0.0309679487179487[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]0.093818181818182[/C][C]Range[/C][C]1.20000000000001[/C][C]Trim Var.[/C][C]0.0627260458839405[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]0.458182539682540[/C][C]Range[/C][C]2.7[/C][C]Trim Var.[/C][C]0.269637096774193[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]0.120285714285714[/C][C]Range[/C][C]1.50000000000000[/C][C]Trim Var.[/C][C]0.0753978494623654[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]0.104206773618539[/C][C]Range[/C][C]1.50000000000000[/C][C]Trim Var.[/C][C]0.0547241379310346[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]0.182348484848486[/C][C]Range[/C][C]1.90000000000001[/C][C]Trim Var.[/C][C]0.101699507389162[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60490&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60490&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)0.429771186440678Range2.3Trim Var.0.333342857142857
V(Y[t],d=1,D=0)0.0388252483927528Range1.1Trim Var.0.0189960784313725
V(Y[t],d=2,D=0)0.0422534785238959Range0.900000000000001Trim Var.0.0267918367346938
V(Y[t],d=3,D=0)0.0829573934837092Range1.5Trim Var.0.0481019607843137
V(Y[t],d=0,D=1)0.283364361702128Range2.2Trim Var.0.138677462887989
V(Y[t],d=1,D=1)0.0708510638297872Range1.3Trim Var.0.0336951219512195
V(Y[t],d=2,D=1)0.0615507246376812Range1.20000000000000Trim Var.0.0309679487179487
V(Y[t],d=3,D=1)0.093818181818182Range1.20000000000001Trim Var.0.0627260458839405
V(Y[t],d=0,D=2)0.458182539682540Range2.7Trim Var.0.269637096774193
V(Y[t],d=1,D=2)0.120285714285714Range1.50000000000000Trim Var.0.0753978494623654
V(Y[t],d=2,D=2)0.104206773618539Range1.50000000000000Trim Var.0.0547241379310346
V(Y[t],d=3,D=2)0.182348484848486Range1.90000000000001Trim Var.0.101699507389162


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(x,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')