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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_variancereduction.wasp

Title produced by software

Variance Reduction Matrix

Date of computation

Fri, 27 Nov 2009 09:41:40 -0700

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Nov/27/t1259340461x4l2ivjyfs8rsjn.htm/, Retrieved Mon, 29 Apr 2024 23:58:29 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60989, Retrieved Mon, 29 Apr 2024 23:58:29 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

110

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 Identifying I...] [2009-11-27 16:41:40] [c6e373ff11c42d4585d53e9e88ed5606] [Current]

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Dataseries X:

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Histogram

Boxplots

10.1
9.9
9.8
9.8
9.7
9.5
9.3
9.1
9.0
9.5
10.0
10.2
10.1
10.0
9.9
10.0
9.9
9.7
9.5
9.2
9.0
9.3
9.8
9.8
9.6
9.4
9.3
9.2
9.2
9.0
8.8
8.7
8.7
9.1
9.7
9.8
9.6
9.4
9.4
9.5
9.4
9.3
9.2
9.0
8.9
9.2
9.8
9.9
9.6
9.2
9.1
9.1
9.0
8.9
8.7
8.5
8.3
8.5
8.7
8.4
8.1
7.8
7.7
7.5
7.2
6.8
6.7
6.4
6.3
6.8
7.3
7.1
7.0
6.8
6.6
6.3
6.1
6.1
6.3
6.3
6.0
6.2
6.4
6.8
7.5
7.5
7.6
7.6
7.4
7.3
7.1
6.9
6.8
7.5
7.6
7.8
8.0
8.1
8.2
8.3
8.2
8.0
7.9
7.6
7.6
8.3
8.4
8.4
8.4
8.4
8.6
8.9
8.8
8.3
7.5
7.2
7.4
8.8
9.3
9.3
8.7
8.2
8.3
8.5
8.6
8.5
8.2
8.1
7.9
8.6
8.7
8.7
8.5
8.4
8.5
8.7
8.7
8.6
8.5
8.3
8.0
8.2
8.1
8.1
8.0
7.9
7.9
8.0
8.0
7.9
8.0
7.7
7.2
7.5
7.3
7.0
7.0
7.0
7.2
7.3
7.1
6.8
6.4
6.1
6.5
7.7
7.9
7.5
6.9
6.6
6.9
7.7
8.0
8.0
7.7
7.3
7.4
8.1
8.3
8.2

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60989&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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60989&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60989&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Variance Reduction Matrix
V(Y[t],d=0,D=0)	1.11422067039106	Range	4.2	Trim Var.	0.815128881987578
V(Y[t],d=1,D=0)	0.094100182035026	Range	2.2	Trim Var.	0.0443675314465409
V(Y[t],d=2,D=0)	0.111242620453247	Range	2.2	Trim Var.	0.0580310534591195
V(Y[t],d=3,D=0)	0.222267591165896	Range	3.1	Trim Var.	0.0917411034153332
V(Y[t],d=0,D=1)	0.597479327060165	Range	3.4	Trim Var.	0.375164157446037
V(Y[t],d=1,D=1)	0.0730546136642378	Range	1.6	Trim Var.	0.0326310538726646
V(Y[t],d=2,D=1)	0.0712712668857248	Range	1.50000000000000	Trim Var.	0.0350798299480397
V(Y[t],d=3,D=1)	0.127311160384331	Range	2.00000000000000	Trim Var.	0.0662995061038115
V(Y[t],d=0,D=2)	0.996100496277916	Range	4.6	Trim Var.	0.642505138746146
V(Y[t],d=1,D=2)	0.189654796816087	Range	2.6	Trim Var.	0.0914566804189145
V(Y[t],d=2,D=2)	0.187043544690604	Range	2.3	Trim Var.	0.104231460911880
V(Y[t],d=3,D=2)	0.337747678018576	Range	3.2	Trim Var.	0.191903177329326

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 1.11422067039106 & Range & 4.2 & Trim Var. & 0.815128881987578 \tabularnewline
V(Y[t],d=1,D=0) & 0.094100182035026 & Range & 2.2 & Trim Var. & 0.0443675314465409 \tabularnewline
V(Y[t],d=2,D=0) & 0.111242620453247 & Range & 2.2 & Trim Var. & 0.0580310534591195 \tabularnewline
V(Y[t],d=3,D=0) & 0.222267591165896 & Range & 3.1 & Trim Var. & 0.0917411034153332 \tabularnewline
V(Y[t],d=0,D=1) & 0.597479327060165 & Range & 3.4 & Trim Var. & 0.375164157446037 \tabularnewline
V(Y[t],d=1,D=1) & 0.0730546136642378 & Range & 1.6 & Trim Var. & 0.0326310538726646 \tabularnewline
V(Y[t],d=2,D=1) & 0.0712712668857248 & Range & 1.50000000000000 & Trim Var. & 0.0350798299480397 \tabularnewline
V(Y[t],d=3,D=1) & 0.127311160384331 & Range & 2.00000000000000 & Trim Var. & 0.0662995061038115 \tabularnewline
V(Y[t],d=0,D=2) & 0.996100496277916 & Range & 4.6 & Trim Var. & 0.642505138746146 \tabularnewline
V(Y[t],d=1,D=2) & 0.189654796816087 & Range & 2.6 & Trim Var. & 0.0914566804189145 \tabularnewline
V(Y[t],d=2,D=2) & 0.187043544690604 & Range & 2.3 & Trim Var. & 0.104231460911880 \tabularnewline
V(Y[t],d=3,D=2) & 0.337747678018576 & Range & 3.2 & Trim Var. & 0.191903177329326 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60989&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]1.11422067039106[/C][C]Range[/C][C]4.2[/C][C]Trim Var.[/C][C]0.815128881987578[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]0.094100182035026[/C][C]Range[/C][C]2.2[/C][C]Trim Var.[/C][C]0.0443675314465409[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]0.111242620453247[/C][C]Range[/C][C]2.2[/C][C]Trim Var.[/C][C]0.0580310534591195[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]0.222267591165896[/C][C]Range[/C][C]3.1[/C][C]Trim Var.[/C][C]0.0917411034153332[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]0.597479327060165[/C][C]Range[/C][C]3.4[/C][C]Trim Var.[/C][C]0.375164157446037[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.0730546136642378[/C][C]Range[/C][C]1.6[/C][C]Trim Var.[/C][C]0.0326310538726646[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]0.0712712668857248[/C][C]Range[/C][C]1.50000000000000[/C][C]Trim Var.[/C][C]0.0350798299480397[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]0.127311160384331[/C][C]Range[/C][C]2.00000000000000[/C][C]Trim Var.[/C][C]0.0662995061038115[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]0.996100496277916[/C][C]Range[/C][C]4.6[/C][C]Trim Var.[/C][C]0.642505138746146[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]0.189654796816087[/C][C]Range[/C][C]2.6[/C][C]Trim Var.[/C][C]0.0914566804189145[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]0.187043544690604[/C][C]Range[/C][C]2.3[/C][C]Trim Var.[/C][C]0.104231460911880[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]0.337747678018576[/C][C]Range[/C][C]3.2[/C][C]Trim Var.[/C][C]0.191903177329326[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60989&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60989&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)	1.11422067039106	Range	4.2	Trim Var.	0.815128881987578
V(Y[t],d=1,D=0)	0.094100182035026	Range	2.2	Trim Var.	0.0443675314465409
V(Y[t],d=2,D=0)	0.111242620453247	Range	2.2	Trim Var.	0.0580310534591195
V(Y[t],d=3,D=0)	0.222267591165896	Range	3.1	Trim Var.	0.0917411034153332
V(Y[t],d=0,D=1)	0.597479327060165	Range	3.4	Trim Var.	0.375164157446037
V(Y[t],d=1,D=1)	0.0730546136642378	Range	1.6	Trim Var.	0.0326310538726646
V(Y[t],d=2,D=1)	0.0712712668857248	Range	1.50000000000000	Trim Var.	0.0350798299480397
V(Y[t],d=3,D=1)	0.127311160384331	Range	2.00000000000000	Trim Var.	0.0662995061038115
V(Y[t],d=0,D=2)	0.996100496277916	Range	4.6	Trim Var.	0.642505138746146
V(Y[t],d=1,D=2)	0.189654796816087	Range	2.6	Trim Var.	0.0914566804189145
V(Y[t],d=2,D=2)	0.187043544690604	Range	2.3	Trim Var.	0.104231460911880
V(Y[t],d=3,D=2)	0.337747678018576	Range	3.2	Trim Var.	0.191903177329326

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')

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Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code