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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 computationWed, 25 Nov 2009 05:02:27 -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/Nov/25/t1259150730v50mxdj2ikitk5p.htm/, Retrieved Tue, 07 May 2024 14:53:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59348, Retrieved Tue, 07 May 2024 14:53:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsworkshop 8
Estimated Impact175

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] [workshop 8] [2009-11-25 12:02:27] [6198946fb53eb5eb18db46bb758f7fde] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.6348
0.634
0.62915
0.62168
0.61328
0.6089
0.60857
0.62672
0.62291
0.62393
0.61838
0.62012
0.61659
0.6116
0.61573
0.61407
0.62823
0.64405
0.6387
0.63633
0.63059
0.62994
0.63709
0.64217
0.65711
0.66977
0.68255
0.68902
0.71322
0.70224
0.70045
0.69919
0.69693
0.69763
0.69278
0.70196
0.69215
0.6769
0.67124
0.66532
0.67157
0.66428
0.66576
0.66942
0.6813
0.69144
0.69862
0.695
0.69867
0.68968
0.69233
0.68293
0.68399
0.66895
0.68756
0.68527
0.6776
0.68137
0.67933
0.67922

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=59348&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=59348&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59348&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)0.00101147875412429Range0.10465Trim Var.0.00086152703078267
V(Y[t],d=1,D=0)7.30827277615429e-05Range0.0394500000000001Trim Var.4.65381343976778e-05
V(Y[t],d=2,D=0)0.000135018247217181Range0.0688299999999998Trim Var.7.32982954751131e-05
V(Y[t],d=3,D=0)0.000432361307581453Range0.104299999999999Trim Var.0.000232390375294118
V(Y[t],d=0,D=1)0.00111180612322695Range0.12664Trim Var.0.000793058607259001
V(Y[t],d=1,D=1)0.000164494401387604Range0.05047Trim Var.0.000104713809390244
V(Y[t],d=2,D=1)0.000217965379710145Range0.0672000000000001Trim Var.0.000121679240961539
V(Y[t],d=3,D=1)0.000608711297676769Range0.115160000000000Trim Var.0.000333141374493927
V(Y[t],d=0,D=2)0.00393510793357143Range0.2092Trim Var.0.00318072465554435
V(Y[t],d=1,D=2)0.000526687988235295Range0.0852300000000001Trim Var.0.00036838273827957
V(Y[t],d=2,D=2)0.000701831717023175Range0.102460000000000Trim Var.0.000448369100689656
V(Y[t],d=3,D=2)0.00197766454375000Range0.185320000000001Trim Var.0.00118677823226601

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 0.00101147875412429 & Range & 0.10465 & Trim Var. & 0.00086152703078267 \tabularnewline
V(Y[t],d=1,D=0) & 7.30827277615429e-05 & Range & 0.0394500000000001 & Trim Var. & 4.65381343976778e-05 \tabularnewline
V(Y[t],d=2,D=0) & 0.000135018247217181 & Range & 0.0688299999999998 & Trim Var. & 7.32982954751131e-05 \tabularnewline
V(Y[t],d=3,D=0) & 0.000432361307581453 & Range & 0.104299999999999 & Trim Var. & 0.000232390375294118 \tabularnewline
V(Y[t],d=0,D=1) & 0.00111180612322695 & Range & 0.12664 & Trim Var. & 0.000793058607259001 \tabularnewline
V(Y[t],d=1,D=1) & 0.000164494401387604 & Range & 0.05047 & Trim Var. & 0.000104713809390244 \tabularnewline
V(Y[t],d=2,D=1) & 0.000217965379710145 & Range & 0.0672000000000001 & Trim Var. & 0.000121679240961539 \tabularnewline
V(Y[t],d=3,D=1) & 0.000608711297676769 & Range & 0.115160000000000 & Trim Var. & 0.000333141374493927 \tabularnewline
V(Y[t],d=0,D=2) & 0.00393510793357143 & Range & 0.2092 & Trim Var. & 0.00318072465554435 \tabularnewline
V(Y[t],d=1,D=2) & 0.000526687988235295 & Range & 0.0852300000000001 & Trim Var. & 0.00036838273827957 \tabularnewline
V(Y[t],d=2,D=2) & 0.000701831717023175 & Range & 0.102460000000000 & Trim Var. & 0.000448369100689656 \tabularnewline
V(Y[t],d=3,D=2) & 0.00197766454375000 & Range & 0.185320000000001 & Trim Var. & 0.00118677823226601 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59348&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]0.00101147875412429[/C][C]Range[/C][C]0.10465[/C][C]Trim Var.[/C][C]0.00086152703078267[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]7.30827277615429e-05[/C][C]Range[/C][C]0.0394500000000001[/C][C]Trim Var.[/C][C]4.65381343976778e-05[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]0.000135018247217181[/C][C]Range[/C][C]0.0688299999999998[/C][C]Trim Var.[/C][C]7.32982954751131e-05[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]0.000432361307581453[/C][C]Range[/C][C]0.104299999999999[/C][C]Trim Var.[/C][C]0.000232390375294118[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]0.00111180612322695[/C][C]Range[/C][C]0.12664[/C][C]Trim Var.[/C][C]0.000793058607259001[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.000164494401387604[/C][C]Range[/C][C]0.05047[/C][C]Trim Var.[/C][C]0.000104713809390244[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]0.000217965379710145[/C][C]Range[/C][C]0.0672000000000001[/C][C]Trim Var.[/C][C]0.000121679240961539[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]0.000608711297676769[/C][C]Range[/C][C]0.115160000000000[/C][C]Trim Var.[/C][C]0.000333141374493927[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]0.00393510793357143[/C][C]Range[/C][C]0.2092[/C][C]Trim Var.[/C][C]0.00318072465554435[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]0.000526687988235295[/C][C]Range[/C][C]0.0852300000000001[/C][C]Trim Var.[/C][C]0.00036838273827957[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]0.000701831717023175[/C][C]Range[/C][C]0.102460000000000[/C][C]Trim Var.[/C][C]0.000448369100689656[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]0.00197766454375000[/C][C]Range[/C][C]0.185320000000001[/C][C]Trim Var.[/C][C]0.00118677823226601[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59348&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59348&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)0.00101147875412429Range0.10465Trim Var.0.00086152703078267
V(Y[t],d=1,D=0)7.30827277615429e-05Range0.0394500000000001Trim Var.4.65381343976778e-05
V(Y[t],d=2,D=0)0.000135018247217181Range0.0688299999999998Trim Var.7.32982954751131e-05
V(Y[t],d=3,D=0)0.000432361307581453Range0.104299999999999Trim Var.0.000232390375294118
V(Y[t],d=0,D=1)0.00111180612322695Range0.12664Trim Var.0.000793058607259001
V(Y[t],d=1,D=1)0.000164494401387604Range0.05047Trim Var.0.000104713809390244
V(Y[t],d=2,D=1)0.000217965379710145Range0.0672000000000001Trim Var.0.000121679240961539
V(Y[t],d=3,D=1)0.000608711297676769Range0.115160000000000Trim Var.0.000333141374493927
V(Y[t],d=0,D=2)0.00393510793357143Range0.2092Trim Var.0.00318072465554435
V(Y[t],d=1,D=2)0.000526687988235295Range0.0852300000000001Trim Var.0.00036838273827957
V(Y[t],d=2,D=2)0.000701831717023175Range0.102460000000000Trim Var.0.000448369100689656
V(Y[t],d=3,D=2)0.00197766454375000Range0.185320000000001Trim Var.0.00118677823226601


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')