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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 computationFri, 04 Dec 2009 05:09:51 -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/04/t1259928657zntalru4xle4nww.htm/, Retrieved Sat, 27 Apr 2024 23:26:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63359, Retrieved Sat, 27 Apr 2024 23:26:59 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact135

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] [] [2009-11-23 15:40:52] [5d885a68c2332cc44f6191ec94766bfa]
-    D            [Variance Reduction Matrix] [VRM] [2009-12-04 12:09:51] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
564
581
597
587
536
524
537
536
533
528
516
502
506
518
534
528
478
469
490
493
508
517
514
510
527
542
565
555
499
511
526
532
549
561
557
566
588
620
626
620
573
573
574
580
590
593
597
595
612
628
629
621
569
567
573
584
589
591
595
594

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=63359&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=63359&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63359&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)1696.88446327684Range160Trim Var.1258.09119496855
V(Y[t],d=1,D=0)352.116306253653Range88Trim Var.186.986937590711
V(Y[t],d=2,D=0)529.516031457955Range114Trim Var.290.604449472097
V(Y[t],d=3,D=0)1242.17355889724Range179Trim Var.619.023529411765
V(Y[t],d=0,D=1)1535.13785460993Range141Trim Var.1091.29442508711
V(Y[t],d=1,D=1)75.6928769657724Range38Trim Var.42.4951219512195
V(Y[t],d=2,D=1)132.915942028986Range61Trim Var.55.9942307692308
V(Y[t],d=3,D=1)423.446464646465Range109Trim Var.187.850202429150
V(Y[t],d=0,D=2)3132.35158730159Range175Trim Var.2607.16129032258
V(Y[t],d=1,D=2)187.927731092437Range52Trim Var.121.984946236559
V(Y[t],d=2,D=2)448.713012477718Range93Trim Var.276.047126436782
V(Y[t],d=3,D=2)1463.42613636364Range136Trim Var.1037.32019704433

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 1696.88446327684 & Range & 160 & Trim Var. & 1258.09119496855 \tabularnewline
V(Y[t],d=1,D=0) & 352.116306253653 & Range & 88 & Trim Var. & 186.986937590711 \tabularnewline
V(Y[t],d=2,D=0) & 529.516031457955 & Range & 114 & Trim Var. & 290.604449472097 \tabularnewline
V(Y[t],d=3,D=0) & 1242.17355889724 & Range & 179 & Trim Var. & 619.023529411765 \tabularnewline
V(Y[t],d=0,D=1) & 1535.13785460993 & Range & 141 & Trim Var. & 1091.29442508711 \tabularnewline
V(Y[t],d=1,D=1) & 75.6928769657724 & Range & 38 & Trim Var. & 42.4951219512195 \tabularnewline
V(Y[t],d=2,D=1) & 132.915942028986 & Range & 61 & Trim Var. & 55.9942307692308 \tabularnewline
V(Y[t],d=3,D=1) & 423.446464646465 & Range & 109 & Trim Var. & 187.850202429150 \tabularnewline
V(Y[t],d=0,D=2) & 3132.35158730159 & Range & 175 & Trim Var. & 2607.16129032258 \tabularnewline
V(Y[t],d=1,D=2) & 187.927731092437 & Range & 52 & Trim Var. & 121.984946236559 \tabularnewline
V(Y[t],d=2,D=2) & 448.713012477718 & Range & 93 & Trim Var. & 276.047126436782 \tabularnewline
V(Y[t],d=3,D=2) & 1463.42613636364 & Range & 136 & Trim Var. & 1037.32019704433 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63359&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]1696.88446327684[/C][C]Range[/C][C]160[/C][C]Trim Var.[/C][C]1258.09119496855[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]352.116306253653[/C][C]Range[/C][C]88[/C][C]Trim Var.[/C][C]186.986937590711[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]529.516031457955[/C][C]Range[/C][C]114[/C][C]Trim Var.[/C][C]290.604449472097[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]1242.17355889724[/C][C]Range[/C][C]179[/C][C]Trim Var.[/C][C]619.023529411765[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]1535.13785460993[/C][C]Range[/C][C]141[/C][C]Trim Var.[/C][C]1091.29442508711[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]75.6928769657724[/C][C]Range[/C][C]38[/C][C]Trim Var.[/C][C]42.4951219512195[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]132.915942028986[/C][C]Range[/C][C]61[/C][C]Trim Var.[/C][C]55.9942307692308[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]423.446464646465[/C][C]Range[/C][C]109[/C][C]Trim Var.[/C][C]187.850202429150[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]3132.35158730159[/C][C]Range[/C][C]175[/C][C]Trim Var.[/C][C]2607.16129032258[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]187.927731092437[/C][C]Range[/C][C]52[/C][C]Trim Var.[/C][C]121.984946236559[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]448.713012477718[/C][C]Range[/C][C]93[/C][C]Trim Var.[/C][C]276.047126436782[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]1463.42613636364[/C][C]Range[/C][C]136[/C][C]Trim Var.[/C][C]1037.32019704433[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63359&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63359&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)1696.88446327684Range160Trim Var.1258.09119496855
V(Y[t],d=1,D=0)352.116306253653Range88Trim Var.186.986937590711
V(Y[t],d=2,D=0)529.516031457955Range114Trim Var.290.604449472097
V(Y[t],d=3,D=0)1242.17355889724Range179Trim Var.619.023529411765
V(Y[t],d=0,D=1)1535.13785460993Range141Trim Var.1091.29442508711
V(Y[t],d=1,D=1)75.6928769657724Range38Trim Var.42.4951219512195
V(Y[t],d=2,D=1)132.915942028986Range61Trim Var.55.9942307692308
V(Y[t],d=3,D=1)423.446464646465Range109Trim Var.187.850202429150
V(Y[t],d=0,D=2)3132.35158730159Range175Trim Var.2607.16129032258
V(Y[t],d=1,D=2)187.927731092437Range52Trim Var.121.984946236559
V(Y[t],d=2,D=2)448.713012477718Range93Trim Var.276.047126436782
V(Y[t],d=3,D=2)1463.42613636364Range136Trim Var.1037.32019704433


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')