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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, 12 Dec 2009 03:41:15 -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/12/t12606145203fh6kn5j1a8d8pw.htm/, Retrieved Mon, 29 Apr 2024 11:57:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=66869, Retrieved Mon, 29 Apr 2024 11:57:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact152

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] [variance reductio...] [2009-11-26 16:20:43] [ed603017d2bee8fbd82b6d5ec04e12c3]
-    D          [Variance Reduction Matrix] [Workshop8] [2009-11-27 11:16:35] [34b80aeb109c116fd63bf2eb7493a276]
-    D              [Variance Reduction Matrix] [methode2] [2009-12-12 10:41:15] [307139c5e328127f586f26d5bcc435d8] [Current]
-    D                [Variance Reduction Matrix] [methode 2] [2009-12-14 09:00:06] [34b80aeb109c116fd63bf2eb7493a276]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
6.3
6.1
6.1
6.3
6.3
6
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
8.1
8.2
8.3
8.2
8
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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=66869&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]0 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=66869&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66869&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 time0 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Variance Reduction Matrix
V(Y[t],d=0,D=0)0.72572131147541Range3.3Trim Var.0.473861236802413
V(Y[t],d=1,D=0)0.118711864406780Range2.2Trim Var.0.0419117647058823
V(Y[t],d=2,D=0)0.152711864406780Range2.1Trim Var.0.0774170437405733
V(Y[t],d=3,D=0)0.340172413793104Range3.1Trim Var.0.156117647058824
V(Y[t],d=0,D=1)0.267108843537415Range1.90000000000000Trim Var.0.169547038327526
V(Y[t],d=1,D=1)0.0958466312056739Range1.4Trim Var.0.0532868757259002
V(Y[t],d=2,D=1)0.100000000000000Range1.30000000000000Trim Var.0.0605000000000002
V(Y[t],d=3,D=1)0.175772946859904Range2.00000000000000Trim Var.0.0886923076923082
V(Y[t],d=0,D=2)0.407582582582583Range2.8Trim Var.0.227973484848485
V(Y[t],d=1,D=2)0.265714285714286Range2.6Trim Var.0.137258064516129
V(Y[t],d=2,D=2)0.271176470588236Range2.00000000000001Trim Var.0.192322580645161
V(Y[t],d=3,D=2)0.499688057041Range3.00000000000001Trim Var.0.304091954022989

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 0.72572131147541 & Range & 3.3 & Trim Var. & 0.473861236802413 \tabularnewline
V(Y[t],d=1,D=0) & 0.118711864406780 & Range & 2.2 & Trim Var. & 0.0419117647058823 \tabularnewline
V(Y[t],d=2,D=0) & 0.152711864406780 & Range & 2.1 & Trim Var. & 0.0774170437405733 \tabularnewline
V(Y[t],d=3,D=0) & 0.340172413793104 & Range & 3.1 & Trim Var. & 0.156117647058824 \tabularnewline
V(Y[t],d=0,D=1) & 0.267108843537415 & Range & 1.90000000000000 & Trim Var. & 0.169547038327526 \tabularnewline
V(Y[t],d=1,D=1) & 0.0958466312056739 & Range & 1.4 & Trim Var. & 0.0532868757259002 \tabularnewline
V(Y[t],d=2,D=1) & 0.100000000000000 & Range & 1.30000000000000 & Trim Var. & 0.0605000000000002 \tabularnewline
V(Y[t],d=3,D=1) & 0.175772946859904 & Range & 2.00000000000000 & Trim Var. & 0.0886923076923082 \tabularnewline
V(Y[t],d=0,D=2) & 0.407582582582583 & Range & 2.8 & Trim Var. & 0.227973484848485 \tabularnewline
V(Y[t],d=1,D=2) & 0.265714285714286 & Range & 2.6 & Trim Var. & 0.137258064516129 \tabularnewline
V(Y[t],d=2,D=2) & 0.271176470588236 & Range & 2.00000000000001 & Trim Var. & 0.192322580645161 \tabularnewline
V(Y[t],d=3,D=2) & 0.499688057041 & Range & 3.00000000000001 & Trim Var. & 0.304091954022989 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=66869&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]0.72572131147541[/C][C]Range[/C][C]3.3[/C][C]Trim Var.[/C][C]0.473861236802413[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]0.118711864406780[/C][C]Range[/C][C]2.2[/C][C]Trim Var.[/C][C]0.0419117647058823[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]0.152711864406780[/C][C]Range[/C][C]2.1[/C][C]Trim Var.[/C][C]0.0774170437405733[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]0.340172413793104[/C][C]Range[/C][C]3.1[/C][C]Trim Var.[/C][C]0.156117647058824[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]0.267108843537415[/C][C]Range[/C][C]1.90000000000000[/C][C]Trim Var.[/C][C]0.169547038327526[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.0958466312056739[/C][C]Range[/C][C]1.4[/C][C]Trim Var.[/C][C]0.0532868757259002[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]0.100000000000000[/C][C]Range[/C][C]1.30000000000000[/C][C]Trim Var.[/C][C]0.0605000000000002[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]0.175772946859904[/C][C]Range[/C][C]2.00000000000000[/C][C]Trim Var.[/C][C]0.0886923076923082[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]0.407582582582583[/C][C]Range[/C][C]2.8[/C][C]Trim Var.[/C][C]0.227973484848485[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]0.265714285714286[/C][C]Range[/C][C]2.6[/C][C]Trim Var.[/C][C]0.137258064516129[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]0.271176470588236[/C][C]Range[/C][C]2.00000000000001[/C][C]Trim Var.[/C][C]0.192322580645161[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]0.499688057041[/C][C]Range[/C][C]3.00000000000001[/C][C]Trim Var.[/C][C]0.304091954022989[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=66869&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66869&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)0.72572131147541Range3.3Trim Var.0.473861236802413
V(Y[t],d=1,D=0)0.118711864406780Range2.2Trim Var.0.0419117647058823
V(Y[t],d=2,D=0)0.152711864406780Range2.1Trim Var.0.0774170437405733
V(Y[t],d=3,D=0)0.340172413793104Range3.1Trim Var.0.156117647058824
V(Y[t],d=0,D=1)0.267108843537415Range1.90000000000000Trim Var.0.169547038327526
V(Y[t],d=1,D=1)0.0958466312056739Range1.4Trim Var.0.0532868757259002
V(Y[t],d=2,D=1)0.100000000000000Range1.30000000000000Trim Var.0.0605000000000002
V(Y[t],d=3,D=1)0.175772946859904Range2.00000000000000Trim Var.0.0886923076923082
V(Y[t],d=0,D=2)0.407582582582583Range2.8Trim Var.0.227973484848485
V(Y[t],d=1,D=2)0.265714285714286Range2.6Trim Var.0.137258064516129
V(Y[t],d=2,D=2)0.271176470588236Range2.00000000000001Trim Var.0.192322580645161
V(Y[t],d=3,D=2)0.499688057041Range3.00000000000001Trim Var.0.304091954022989


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')