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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 computationTue, 24 Nov 2009 05:00:42 -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/24/t1259064102ygbi3871036886a.htm/, Retrieved Fri, 15 Nov 2024 00:46:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59013, Retrieved Fri, 15 Nov 2024 00:46:40 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact216
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] [SHW WS8] [2009-11-24 12:00:42] [b7e46d23597387652ca7420fdeb9acca] [Current]
-   PD            [Variance Reduction Matrix] [ws8 model2.1] [2009-11-27 16:46:34] [95cead3ebb75668735f848316249436a]
-   PD              [Variance Reduction Matrix] [paper vrm1] [2009-12-13 15:23:40] [95cead3ebb75668735f848316249436a]
-    D                [Variance Reduction Matrix] [deel2 vrm] [2009-12-13 17:15:37] [95cead3ebb75668735f848316249436a]
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Dataseries X:
8.6
8.5
8.3
7.8
7.8
8
8.6
8.9
8.9
8.6
8.3
8.3
8.3
8.4
8.5
8.4
8.6
8.5
8.5
8.5
8.5
8.5
8.5
8.5
8.5
8.5
8.5
8.5
8.6
8.4
8.1
8
8
8
8
7.9
7.8
7.8
7.9
8.1
8
7.6
7.3
7
6.8
7
7.1
7.2
7.1
6.9
6.7
6.7
6.6
6.9
7.3
7.5
7.3
7.1
6.9
7.1




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=59013&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=59013&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59013&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 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)0.431581920903955Range2.3Trim Var.0.335657142857143
V(Y[t],d=1,D=0)0.0384804208065459Range1.1Trim Var.0.0185960784313725
V(Y[t],d=2,D=0)0.0412008469449486Range0.900000000000001Trim Var.0.0255673469387754
V(Y[t],d=3,D=0)0.0790288220551378Range1.5Trim Var.0.0437019607843137
V(Y[t],d=0,D=1)0.283364361702128Range2.2Trim Var.0.138677462887989
V(Y[t],d=1,D=1)0.0691119333950046Range1.3Trim Var.0.0304993252361673
V(Y[t],d=2,D=1)0.0588840579710145Range1.20000000000000Trim Var.0.0302307692307692
V(Y[t],d=3,D=1)0.0870000000000002Range1.30000000000000Trim Var.0.0519973009446694
V(Y[t],d=0,D=2)0.454Range2.7Trim Var.0.264506048387097
V(Y[t],d=1,D=2)0.115579831932773Range1.50000000000000Trim Var.0.070064516129032
V(Y[t],d=2,D=2)0.0963279857397506Range1.50000000000000Trim Var.0.049609195402299
V(Y[t],d=3,D=2)0.159223484848486Range1.90000000000001Trim Var.0.0814778325123155

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 0.431581920903955 & Range & 2.3 & Trim Var. & 0.335657142857143 \tabularnewline
V(Y[t],d=1,D=0) & 0.0384804208065459 & Range & 1.1 & Trim Var. & 0.0185960784313725 \tabularnewline
V(Y[t],d=2,D=0) & 0.0412008469449486 & Range & 0.900000000000001 & Trim Var. & 0.0255673469387754 \tabularnewline
V(Y[t],d=3,D=0) & 0.0790288220551378 & Range & 1.5 & Trim Var. & 0.0437019607843137 \tabularnewline
V(Y[t],d=0,D=1) & 0.283364361702128 & Range & 2.2 & Trim Var. & 0.138677462887989 \tabularnewline
V(Y[t],d=1,D=1) & 0.0691119333950046 & Range & 1.3 & Trim Var. & 0.0304993252361673 \tabularnewline
V(Y[t],d=2,D=1) & 0.0588840579710145 & Range & 1.20000000000000 & Trim Var. & 0.0302307692307692 \tabularnewline
V(Y[t],d=3,D=1) & 0.0870000000000002 & Range & 1.30000000000000 & Trim Var. & 0.0519973009446694 \tabularnewline
V(Y[t],d=0,D=2) & 0.454 & Range & 2.7 & Trim Var. & 0.264506048387097 \tabularnewline
V(Y[t],d=1,D=2) & 0.115579831932773 & Range & 1.50000000000000 & Trim Var. & 0.070064516129032 \tabularnewline
V(Y[t],d=2,D=2) & 0.0963279857397506 & Range & 1.50000000000000 & Trim Var. & 0.049609195402299 \tabularnewline
V(Y[t],d=3,D=2) & 0.159223484848486 & Range & 1.90000000000001 & Trim Var. & 0.0814778325123155 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59013&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]0.431581920903955[/C][C]Range[/C][C]2.3[/C][C]Trim Var.[/C][C]0.335657142857143[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]0.0384804208065459[/C][C]Range[/C][C]1.1[/C][C]Trim Var.[/C][C]0.0185960784313725[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]0.0412008469449486[/C][C]Range[/C][C]0.900000000000001[/C][C]Trim Var.[/C][C]0.0255673469387754[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]0.0790288220551378[/C][C]Range[/C][C]1.5[/C][C]Trim Var.[/C][C]0.0437019607843137[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]0.283364361702128[/C][C]Range[/C][C]2.2[/C][C]Trim Var.[/C][C]0.138677462887989[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.0691119333950046[/C][C]Range[/C][C]1.3[/C][C]Trim Var.[/C][C]0.0304993252361673[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]0.0588840579710145[/C][C]Range[/C][C]1.20000000000000[/C][C]Trim Var.[/C][C]0.0302307692307692[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]0.0870000000000002[/C][C]Range[/C][C]1.30000000000000[/C][C]Trim Var.[/C][C]0.0519973009446694[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]0.454[/C][C]Range[/C][C]2.7[/C][C]Trim Var.[/C][C]0.264506048387097[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]0.115579831932773[/C][C]Range[/C][C]1.50000000000000[/C][C]Trim Var.[/C][C]0.070064516129032[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]0.0963279857397506[/C][C]Range[/C][C]1.50000000000000[/C][C]Trim Var.[/C][C]0.049609195402299[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]0.159223484848486[/C][C]Range[/C][C]1.90000000000001[/C][C]Trim Var.[/C][C]0.0814778325123155[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59013&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59013&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)0.431581920903955Range2.3Trim Var.0.335657142857143
V(Y[t],d=1,D=0)0.0384804208065459Range1.1Trim Var.0.0185960784313725
V(Y[t],d=2,D=0)0.0412008469449486Range0.900000000000001Trim Var.0.0255673469387754
V(Y[t],d=3,D=0)0.0790288220551378Range1.5Trim Var.0.0437019607843137
V(Y[t],d=0,D=1)0.283364361702128Range2.2Trim Var.0.138677462887989
V(Y[t],d=1,D=1)0.0691119333950046Range1.3Trim Var.0.0304993252361673
V(Y[t],d=2,D=1)0.0588840579710145Range1.20000000000000Trim Var.0.0302307692307692
V(Y[t],d=3,D=1)0.0870000000000002Range1.30000000000000Trim Var.0.0519973009446694
V(Y[t],d=0,D=2)0.454Range2.7Trim Var.0.264506048387097
V(Y[t],d=1,D=2)0.115579831932773Range1.50000000000000Trim Var.0.070064516129032
V(Y[t],d=2,D=2)0.0963279857397506Range1.50000000000000Trim Var.0.049609195402299
V(Y[t],d=3,D=2)0.159223484848486Range1.90000000000001Trim Var.0.0814778325123155



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')