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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 computationSat, 19 Dec 2009 05:52:22 -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/19/t1261227355isg8rk8c142ez7y.htm/, Retrieved Fri, 03 May 2024 23:50:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69559, Retrieved Fri, 03 May 2024 23:50:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsvariance reduction matrix (correcte)
Estimated Impact105

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] [Variance reductio...] [2009-12-19 12:52:22] [8b8f95c5f2993a04d1b74eff1a82c018] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
91,02
91,19
91,53
91,88
92,06
92,32
92,67
92,85
92,82
93,46
93,23
93,54
93,29
93,2
93,6
93,81
94,62
95,22
95,38
95,31
95,3
95,57
95,42
95,53
95,33
95,90
96,06
96,31
96,34
96,49
96,22
96,53
96,50
96,77
96,66
96,58
96,63
97,06
97,73
98,01
97,76
97,49
97,77
97,96
98,23
98,51
98,19
98,37
98,31
98,60
98,97
99,11
99,64
100,03
99,98
100,32
100,44
100,51
101,00
100,88
100,55
100,83
101,51
102,16
102,39
102,54
102,85
103,47
103,57
103,69
103,5
103,47
103,45
103,48
103,93
103,89
104,4
104,79
104,77
105,13
105,26
104,96
104,75
105,01
105,15
105,2
105,77
105,78
106,26
106,13
106,12
106,57
106,44
106,54
107,1
108,1
108,4
108,84
109,62
110,42
110,67
111,66
112,28
112,87
112,18
112,36
112,16
111,49
111,25
111,36
111,74
111,1
111,33
111,25
111,04
110,97
111,31
111,02
111,07
111,36

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=69559&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=69559&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69559&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)40.2017870518207Range21.85Trim Var.32.7844485981308
V(Y[t],d=1,D=0)0.103450833214642Range1.69000000000000Trim Var.0.0622168400634807
V(Y[t],d=2,D=0)0.17430664928292Range2.15000000000001Trim Var.0.116375022461815
V(Y[t],d=3,D=0)0.518538432066017Range3.68999999999998Trim Var.0.345855622710622
V(Y[t],d=0,D=1)1.93214104361371Range8.20000000000002Trim Var.0.638059462719299
V(Y[t],d=1,D=1)0.220660077587727Range2.79000000000001Trim Var.0.110820201567750
V(Y[t],d=2,D=1)0.348910080862534Range3.19000000000001Trim Var.0.196355072463767
V(Y[t],d=3,D=1)1.02137357142857Range5.650Trim Var.0.559153038803176
V(Y[t],d=0,D=2)5.51670542763159Range13.0600000000000Trim Var.2.01432521203831
V(Y[t],d=1,D=2)0.667616618141098Range5.04000000000001Trim Var.0.33670005602241
V(Y[t],d=2,D=2)1.03790314573324Range4.84Trim Var.0.657149168100972
V(Y[t],d=3,D=2)2.99158122954651Range8.89999999999998Trim Var.1.78563558624742

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 40.2017870518207 & Range & 21.85 & Trim Var. & 32.7844485981308 \tabularnewline
V(Y[t],d=1,D=0) & 0.103450833214642 & Range & 1.69000000000000 & Trim Var. & 0.0622168400634807 \tabularnewline
V(Y[t],d=2,D=0) & 0.17430664928292 & Range & 2.15000000000001 & Trim Var. & 0.116375022461815 \tabularnewline
V(Y[t],d=3,D=0) & 0.518538432066017 & Range & 3.68999999999998 & Trim Var. & 0.345855622710622 \tabularnewline
V(Y[t],d=0,D=1) & 1.93214104361371 & Range & 8.20000000000002 & Trim Var. & 0.638059462719299 \tabularnewline
V(Y[t],d=1,D=1) & 0.220660077587727 & Range & 2.79000000000001 & Trim Var. & 0.110820201567750 \tabularnewline
V(Y[t],d=2,D=1) & 0.348910080862534 & Range & 3.19000000000001 & Trim Var. & 0.196355072463767 \tabularnewline
V(Y[t],d=3,D=1) & 1.02137357142857 & Range & 5.650 & Trim Var. & 0.559153038803176 \tabularnewline
V(Y[t],d=0,D=2) & 5.51670542763159 & Range & 13.0600000000000 & Trim Var. & 2.01432521203831 \tabularnewline
V(Y[t],d=1,D=2) & 0.667616618141098 & Range & 5.04000000000001 & Trim Var. & 0.33670005602241 \tabularnewline
V(Y[t],d=2,D=2) & 1.03790314573324 & Range & 4.84 & Trim Var. & 0.657149168100972 \tabularnewline
V(Y[t],d=3,D=2) & 2.99158122954651 & Range & 8.89999999999998 & Trim Var. & 1.78563558624742 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69559&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]40.2017870518207[/C][C]Range[/C][C]21.85[/C][C]Trim Var.[/C][C]32.7844485981308[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]0.103450833214642[/C][C]Range[/C][C]1.69000000000000[/C][C]Trim Var.[/C][C]0.0622168400634807[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]0.17430664928292[/C][C]Range[/C][C]2.15000000000001[/C][C]Trim Var.[/C][C]0.116375022461815[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]0.518538432066017[/C][C]Range[/C][C]3.68999999999998[/C][C]Trim Var.[/C][C]0.345855622710622[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]1.93214104361371[/C][C]Range[/C][C]8.20000000000002[/C][C]Trim Var.[/C][C]0.638059462719299[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.220660077587727[/C][C]Range[/C][C]2.79000000000001[/C][C]Trim Var.[/C][C]0.110820201567750[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]0.348910080862534[/C][C]Range[/C][C]3.19000000000001[/C][C]Trim Var.[/C][C]0.196355072463767[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]1.02137357142857[/C][C]Range[/C][C]5.650[/C][C]Trim Var.[/C][C]0.559153038803176[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]5.51670542763159[/C][C]Range[/C][C]13.0600000000000[/C][C]Trim Var.[/C][C]2.01432521203831[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]0.667616618141098[/C][C]Range[/C][C]5.04000000000001[/C][C]Trim Var.[/C][C]0.33670005602241[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]1.03790314573324[/C][C]Range[/C][C]4.84[/C][C]Trim Var.[/C][C]0.657149168100972[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]2.99158122954651[/C][C]Range[/C][C]8.89999999999998[/C][C]Trim Var.[/C][C]1.78563558624742[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69559&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69559&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)40.2017870518207Range21.85Trim Var.32.7844485981308
V(Y[t],d=1,D=0)0.103450833214642Range1.69000000000000Trim Var.0.0622168400634807
V(Y[t],d=2,D=0)0.17430664928292Range2.15000000000001Trim Var.0.116375022461815
V(Y[t],d=3,D=0)0.518538432066017Range3.68999999999998Trim Var.0.345855622710622
V(Y[t],d=0,D=1)1.93214104361371Range8.20000000000002Trim Var.0.638059462719299
V(Y[t],d=1,D=1)0.220660077587727Range2.79000000000001Trim Var.0.110820201567750
V(Y[t],d=2,D=1)0.348910080862534Range3.19000000000001Trim Var.0.196355072463767
V(Y[t],d=3,D=1)1.02137357142857Range5.650Trim Var.0.559153038803176
V(Y[t],d=0,D=2)5.51670542763159Range13.0600000000000Trim Var.2.01432521203831
V(Y[t],d=1,D=2)0.667616618141098Range5.04000000000001Trim Var.0.33670005602241
V(Y[t],d=2,D=2)1.03790314573324Range4.84Trim Var.0.657149168100972
V(Y[t],d=3,D=2)2.99158122954651Range8.89999999999998Trim Var.1.78563558624742


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')