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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, 16 Dec 2009 08:54:30 -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/Dec/16/t1260978960182ebi6b2jqigjy.htm/, Retrieved Tue, 30 Apr 2024 12:51:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=68445, Retrieved Tue, 30 Apr 2024 12:51:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact156
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] [WS8 Method 2] [2009-11-25 16:22:46] [445b292c553470d9fed8bc2796fd3a00]
-    D          [Variance Reduction Matrix] [ws 8 vrm] [2009-11-25 21:32:07] [134dc66689e3d457a82860db6471d419]
-    D            [Variance Reduction Matrix] [WS 8 Variance Red...] [2009-11-26 20:48:20] [3425351e86519d261a643e224a0c8ee1]
-    D              [Variance Reduction Matrix] [variance reductio...] [2009-12-15 20:03:24] [3425351e86519d261a643e224a0c8ee1]
-    D                  [Variance Reduction Matrix] [] [2009-12-16 15:54:30] [17416e80e7873ecccac25c455c5f767e] [Current]
-    D                    [Variance Reduction Matrix] [VRM] [2009-12-21 01:53:18] [76ab39dc7a55316678260825bd5ad46c]
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Dataseries X:
91,98
91,72
90,27
91,89
92,07
92,92
93,34
93,6
92,41
93,6
93,77
93,6
93,6
93,51
92,66
94,2
94,37
94,45
94,62
94,37
93,43
94,79
94,88
94,79
94,62
94,71
93,77
95,73
95,99
95,82
95,47
95,82
94,71
96,33
96,5
96,16
96,33
96,33
95,05
96,84
96,92
97,44
97,78
97,69
96,67
98,29
98,2
98,71
98,54
98,2
96,92
99,06
99,65
99,82
99,99
100,33
99,31
101,1
101,1
100,93
100,85
100,93
99,6
101,88
101,81
102,38
102,74
102,82
101,72
103,47
102,98
102,68
102,9
103,03
101,29
103,69
103,68
104,2
104,08
104,16
103,05
104,66
104,46
104,95
105,85
106,23
104,86
107,44
108,23
108,45
109,39
110,15
109,13
110,28
110,17
109,99
109,26
109,11
107,06
109,53
108,92
109,24
109,12
109
107,23
109,49
109,04
109,02
109,23




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=68445&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=68445&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68445&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Variance Reduction Matrix
V(Y[t],d=0,D=0)33.3037066089025Range20.01Trim Var.27.0253596649485
V(Y[t],d=1,D=0)0.939709267912772Range4.63Trim Var.0.548160252192983
V(Y[t],d=2,D=0)2.71674939164168Range7.6Trim Var.1.66260194848824
V(Y[t],d=3,D=0)9.13514645103323Range14.0200000000000Trim Var.5.72119918782887
V(Y[t],d=0,D=1)1.97993404209622Range7.97999999999999Trim Var.0.79199294306335
V(Y[t],d=1,D=1)0.235683585526314Range2.73999999999997Trim Var.0.125923296853625
V(Y[t],d=2,D=1)0.400292116461361Range3.30999999999995Trim Var.0.235509299719885
V(Y[t],d=3,D=1)1.2107505033173Range6.09999999999995Trim Var.0.685393961560518
V(Y[t],d=0,D=2)5.6028637815126Range12.73Trim Var.1.85651754954955
V(Y[t],d=1,D=2)0.698713023522658Range4.87999999999995Trim Var.0.335474639022585
V(Y[t],d=2,D=2)1.15864440199822Range5.11999999999998Trim Var.0.682092275494668
V(Y[t],d=3,D=2)3.43629870520923Range9.62999999999997Trim Var.1.9547209507042

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 33.3037066089025 & Range & 20.01 & Trim Var. & 27.0253596649485 \tabularnewline
V(Y[t],d=1,D=0) & 0.939709267912772 & Range & 4.63 & Trim Var. & 0.548160252192983 \tabularnewline
V(Y[t],d=2,D=0) & 2.71674939164168 & Range & 7.6 & Trim Var. & 1.66260194848824 \tabularnewline
V(Y[t],d=3,D=0) & 9.13514645103323 & Range & 14.0200000000000 & Trim Var. & 5.72119918782887 \tabularnewline
V(Y[t],d=0,D=1) & 1.97993404209622 & Range & 7.97999999999999 & Trim Var. & 0.79199294306335 \tabularnewline
V(Y[t],d=1,D=1) & 0.235683585526314 & Range & 2.73999999999997 & Trim Var. & 0.125923296853625 \tabularnewline
V(Y[t],d=2,D=1) & 0.400292116461361 & Range & 3.30999999999995 & Trim Var. & 0.235509299719885 \tabularnewline
V(Y[t],d=3,D=1) & 1.2107505033173 & Range & 6.09999999999995 & Trim Var. & 0.685393961560518 \tabularnewline
V(Y[t],d=0,D=2) & 5.6028637815126 & Range & 12.73 & Trim Var. & 1.85651754954955 \tabularnewline
V(Y[t],d=1,D=2) & 0.698713023522658 & Range & 4.87999999999995 & Trim Var. & 0.335474639022585 \tabularnewline
V(Y[t],d=2,D=2) & 1.15864440199822 & Range & 5.11999999999998 & Trim Var. & 0.682092275494668 \tabularnewline
V(Y[t],d=3,D=2) & 3.43629870520923 & Range & 9.62999999999997 & Trim Var. & 1.9547209507042 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68445&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]33.3037066089025[/C][C]Range[/C][C]20.01[/C][C]Trim Var.[/C][C]27.0253596649485[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]0.939709267912772[/C][C]Range[/C][C]4.63[/C][C]Trim Var.[/C][C]0.548160252192983[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]2.71674939164168[/C][C]Range[/C][C]7.6[/C][C]Trim Var.[/C][C]1.66260194848824[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]9.13514645103323[/C][C]Range[/C][C]14.0200000000000[/C][C]Trim Var.[/C][C]5.72119918782887[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]1.97993404209622[/C][C]Range[/C][C]7.97999999999999[/C][C]Trim Var.[/C][C]0.79199294306335[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.235683585526314[/C][C]Range[/C][C]2.73999999999997[/C][C]Trim Var.[/C][C]0.125923296853625[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]0.400292116461361[/C][C]Range[/C][C]3.30999999999995[/C][C]Trim Var.[/C][C]0.235509299719885[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]1.2107505033173[/C][C]Range[/C][C]6.09999999999995[/C][C]Trim Var.[/C][C]0.685393961560518[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]5.6028637815126[/C][C]Range[/C][C]12.73[/C][C]Trim Var.[/C][C]1.85651754954955[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]0.698713023522658[/C][C]Range[/C][C]4.87999999999995[/C][C]Trim Var.[/C][C]0.335474639022585[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]1.15864440199822[/C][C]Range[/C][C]5.11999999999998[/C][C]Trim Var.[/C][C]0.682092275494668[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]3.43629870520923[/C][C]Range[/C][C]9.62999999999997[/C][C]Trim Var.[/C][C]1.9547209507042[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68445&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68445&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Variance Reduction Matrix
V(Y[t],d=0,D=0)33.3037066089025Range20.01Trim Var.27.0253596649485
V(Y[t],d=1,D=0)0.939709267912772Range4.63Trim Var.0.548160252192983
V(Y[t],d=2,D=0)2.71674939164168Range7.6Trim Var.1.66260194848824
V(Y[t],d=3,D=0)9.13514645103323Range14.0200000000000Trim Var.5.72119918782887
V(Y[t],d=0,D=1)1.97993404209622Range7.97999999999999Trim Var.0.79199294306335
V(Y[t],d=1,D=1)0.235683585526314Range2.73999999999997Trim Var.0.125923296853625
V(Y[t],d=2,D=1)0.400292116461361Range3.30999999999995Trim Var.0.235509299719885
V(Y[t],d=3,D=1)1.2107505033173Range6.09999999999995Trim Var.0.685393961560518
V(Y[t],d=0,D=2)5.6028637815126Range12.73Trim Var.1.85651754954955
V(Y[t],d=1,D=2)0.698713023522658Range4.87999999999995Trim Var.0.335474639022585
V(Y[t],d=2,D=2)1.15864440199822Range5.11999999999998Trim Var.0.682092275494668
V(Y[t],d=3,D=2)3.43629870520923Range9.62999999999997Trim Var.1.9547209507042



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')