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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 computationSun, 21 Dec 2008 15:07:14 -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/2008/Dec/21/t1229897265z2ut7uhtbp0ixzy.htm/, Retrieved Fri, 17 May 2024 05:14:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=35868, Retrieved Fri, 17 May 2024 05:14:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact157

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Box-Cox Linearity Plot] [Box cox linearity...] [2008-12-21 21:47:51] [c5e27150943bc3d623392efb0d98f8d3]
-    D  [Box-Cox Linearity Plot] [Box cox linearity...] [2008-12-21 21:49:45] [c5e27150943bc3d623392efb0d98f8d3]
- RMPD    [Standard Deviation-Mean Plot] [standard deviatio...] [2008-12-21 21:56:51] [c5e27150943bc3d623392efb0d98f8d3]
-    D      [Standard Deviation-Mean Plot] [standard deviatio...] [2008-12-21 21:58:39] [c5e27150943bc3d623392efb0d98f8d3]
- RMPD        [Box-Cox Normality Plot] [box cox normality...] [2008-12-21 22:02:22] [c5e27150943bc3d623392efb0d98f8d3]
-    D          [Box-Cox Normality Plot] [box cox normality...] [2008-12-21 22:04:17] [c5e27150943bc3d623392efb0d98f8d3]
- RM D              [Variance Reduction Matrix] [variance reductio...] [2008-12-21 22:07:14] [25d75405d700c34901b109463a9659f5] [Current]
-    D                [Variance Reduction Matrix] [variance reductio...] [2008-12-21 22:08:53] [4ddbf81f78ea7c738951638c7e93f6ee]
-    D                  [Variance Reduction Matrix] [variance reductio...] [2008-12-21 22:10:18] [4ddbf81f78ea7c738951638c7e93f6ee]
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Dataset

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

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'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35868&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35868&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35868&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'George Udny Yule' @ 72.249.76.132






Variance Reduction Matrix
V(Y[t],d=0,D=0)0.41083615819209Range2.3Trim Var.0.316883298392732
V(Y[t],d=1,D=0)0.0829222676797195Range1.7Trim Var.0.0413876319758672
V(Y[t],d=2,D=0)0.0999516031457955Range1.5Trim Var.0.0563102040816326
V(Y[t],d=3,D=0)0.222293233082707Range2.7Trim Var.0.102337254901961
V(Y[t],d=0,D=1)0.0829222676797195Range1.7Trim Var.0.0413876319758672
V(Y[t],d=1,D=1)0.0999516031457955Range1.5Trim Var.0.0563102040816326
V(Y[t],d=2,D=1)0.222293233082707Range2.7Trim Var.0.102337254901961
V(Y[t],d=3,D=1)0.684974025974026Range4.3Trim Var.0.303444897959184
V(Y[t],d=0,D=2)0.0999516031457955Range1.5Trim Var.0.0563102040816326
V(Y[t],d=1,D=2)0.222293233082707Range2.7Trim Var.0.102337254901961
V(Y[t],d=2,D=2)0.684974025974026Range4.3Trim Var.0.303444897959184
V(Y[t],d=3,D=2)2.34905723905724Range8.4Trim Var.1.13704931972789

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 0.41083615819209 & Range & 2.3 & Trim Var. & 0.316883298392732 \tabularnewline
V(Y[t],d=1,D=0) & 0.0829222676797195 & Range & 1.7 & Trim Var. & 0.0413876319758672 \tabularnewline
V(Y[t],d=2,D=0) & 0.0999516031457955 & Range & 1.5 & Trim Var. & 0.0563102040816326 \tabularnewline
V(Y[t],d=3,D=0) & 0.222293233082707 & Range & 2.7 & Trim Var. & 0.102337254901961 \tabularnewline
V(Y[t],d=0,D=1) & 0.0829222676797195 & Range & 1.7 & Trim Var. & 0.0413876319758672 \tabularnewline
V(Y[t],d=1,D=1) & 0.0999516031457955 & Range & 1.5 & Trim Var. & 0.0563102040816326 \tabularnewline
V(Y[t],d=2,D=1) & 0.222293233082707 & Range & 2.7 & Trim Var. & 0.102337254901961 \tabularnewline
V(Y[t],d=3,D=1) & 0.684974025974026 & Range & 4.3 & Trim Var. & 0.303444897959184 \tabularnewline
V(Y[t],d=0,D=2) & 0.0999516031457955 & Range & 1.5 & Trim Var. & 0.0563102040816326 \tabularnewline
V(Y[t],d=1,D=2) & 0.222293233082707 & Range & 2.7 & Trim Var. & 0.102337254901961 \tabularnewline
V(Y[t],d=2,D=2) & 0.684974025974026 & Range & 4.3 & Trim Var. & 0.303444897959184 \tabularnewline
V(Y[t],d=3,D=2) & 2.34905723905724 & Range & 8.4 & Trim Var. & 1.13704931972789 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35868&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]0.41083615819209[/C][C]Range[/C][C]2.3[/C][C]Trim Var.[/C][C]0.316883298392732[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]0.0829222676797195[/C][C]Range[/C][C]1.7[/C][C]Trim Var.[/C][C]0.0413876319758672[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]0.0999516031457955[/C][C]Range[/C][C]1.5[/C][C]Trim Var.[/C][C]0.0563102040816326[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]0.222293233082707[/C][C]Range[/C][C]2.7[/C][C]Trim Var.[/C][C]0.102337254901961[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]0.0829222676797195[/C][C]Range[/C][C]1.7[/C][C]Trim Var.[/C][C]0.0413876319758672[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.0999516031457955[/C][C]Range[/C][C]1.5[/C][C]Trim Var.[/C][C]0.0563102040816326[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]0.222293233082707[/C][C]Range[/C][C]2.7[/C][C]Trim Var.[/C][C]0.102337254901961[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]0.684974025974026[/C][C]Range[/C][C]4.3[/C][C]Trim Var.[/C][C]0.303444897959184[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]0.0999516031457955[/C][C]Range[/C][C]1.5[/C][C]Trim Var.[/C][C]0.0563102040816326[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]0.222293233082707[/C][C]Range[/C][C]2.7[/C][C]Trim Var.[/C][C]0.102337254901961[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]0.684974025974026[/C][C]Range[/C][C]4.3[/C][C]Trim Var.[/C][C]0.303444897959184[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]2.34905723905724[/C][C]Range[/C][C]8.4[/C][C]Trim Var.[/C][C]1.13704931972789[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35868&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35868&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)0.41083615819209Range2.3Trim Var.0.316883298392732
V(Y[t],d=1,D=0)0.0829222676797195Range1.7Trim Var.0.0413876319758672
V(Y[t],d=2,D=0)0.0999516031457955Range1.5Trim Var.0.0563102040816326
V(Y[t],d=3,D=0)0.222293233082707Range2.7Trim Var.0.102337254901961
V(Y[t],d=0,D=1)0.0829222676797195Range1.7Trim Var.0.0413876319758672
V(Y[t],d=1,D=1)0.0999516031457955Range1.5Trim Var.0.0563102040816326
V(Y[t],d=2,D=1)0.222293233082707Range2.7Trim Var.0.102337254901961
V(Y[t],d=3,D=1)0.684974025974026Range4.3Trim Var.0.303444897959184
V(Y[t],d=0,D=2)0.0999516031457955Range1.5Trim Var.0.0563102040816326
V(Y[t],d=1,D=2)0.222293233082707Range2.7Trim Var.0.102337254901961
V(Y[t],d=2,D=2)0.684974025974026Range4.3Trim Var.0.303444897959184
V(Y[t],d=3,D=2)2.34905723905724Range8.4Trim Var.1.13704931972789


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
Parameters (R input):
par1 = 1 ;
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')