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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_variancereduction.wasp
Title produced by softwareVariance Reduction Matrix
Date of computationTue, 01 Dec 2009 07:51:55 -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/01/t1259679170bsubjrixd9zd4rs.htm/, Retrieved Fri, 26 Apr 2024 13:02:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62072, Retrieved Fri, 26 Apr 2024 13:02:50 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordscvm
Estimated Impact134

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       [(Partial) Autocorrelation Function] [Identifying Integ...] [2009-11-22 12:16:10] [b98453cac15ba1066b407e146608df68]
-    D        [(Partial) Autocorrelation Function] [BBWS8-ACF1] [2009-11-28 15:24:25] [408e92805dcb18620260f240a7fb9d53]
-   P           [(Partial) Autocorrelation Function] [BBWS8-ACF2] [2009-11-28 15:29:29] [408e92805dcb18620260f240a7fb9d53]
F   P             [(Partial) Autocorrelation Function] [BBWS8-ACF3] [2009-11-28 15:34:32] [408e92805dcb18620260f240a7fb9d53]
- RMPD                [Variance Reduction Matrix] [W8: VRM] [2009-12-01 14:51:55] [a54c891e28140f8069e5593fadde9f72] [Current]
-   PD                  [Variance Reduction Matrix] [review Ws 8 vrm] [2009-12-04 17:24:14] [12f02da0296cb21dc23d82ae014a8b71]
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Dataset

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

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=62072&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=62072&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62072&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)0.287830601092896Range2.1Trim Var.0.156955782312925
V(Y[t],d=1,D=0)0.064550847457627Range1.3Trim Var.0.0327413273001508
V(Y[t],d=2,D=0)0.066206896551724Range1.1Trim Var.0.0404939668174962
V(Y[t],d=3,D=0)0.135075620084694Range1.9Trim Var.0.0699660633484162
V(Y[t],d=0,D=1)0.064550847457627Range1.3Trim Var.0.0327413273001508
V(Y[t],d=1,D=1)0.066206896551724Range1.1Trim Var.0.0404939668174962
V(Y[t],d=2,D=1)0.135075620084694Range1.9Trim Var.0.0699660633484162
V(Y[t],d=3,D=1)0.400307017543859Range3Trim Var.0.215796078431372
V(Y[t],d=0,D=2)0.066206896551724Range1.1Trim Var.0.0404939668174962
V(Y[t],d=1,D=2)0.135075620084694Range1.9Trim Var.0.0699660633484162
V(Y[t],d=2,D=2)0.400307017543859Range3Trim Var.0.215796078431372
V(Y[t],d=3,D=2)1.37288311688311Range5.59999999999999Trim Var.0.740391836734693

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 0.287830601092896 & Range & 2.1 & Trim Var. & 0.156955782312925 \tabularnewline
V(Y[t],d=1,D=0) & 0.064550847457627 & Range & 1.3 & Trim Var. & 0.0327413273001508 \tabularnewline
V(Y[t],d=2,D=0) & 0.066206896551724 & Range & 1.1 & Trim Var. & 0.0404939668174962 \tabularnewline
V(Y[t],d=3,D=0) & 0.135075620084694 & Range & 1.9 & Trim Var. & 0.0699660633484162 \tabularnewline
V(Y[t],d=0,D=1) & 0.064550847457627 & Range & 1.3 & Trim Var. & 0.0327413273001508 \tabularnewline
V(Y[t],d=1,D=1) & 0.066206896551724 & Range & 1.1 & Trim Var. & 0.0404939668174962 \tabularnewline
V(Y[t],d=2,D=1) & 0.135075620084694 & Range & 1.9 & Trim Var. & 0.0699660633484162 \tabularnewline
V(Y[t],d=3,D=1) & 0.400307017543859 & Range & 3 & Trim Var. & 0.215796078431372 \tabularnewline
V(Y[t],d=0,D=2) & 0.066206896551724 & Range & 1.1 & Trim Var. & 0.0404939668174962 \tabularnewline
V(Y[t],d=1,D=2) & 0.135075620084694 & Range & 1.9 & Trim Var. & 0.0699660633484162 \tabularnewline
V(Y[t],d=2,D=2) & 0.400307017543859 & Range & 3 & Trim Var. & 0.215796078431372 \tabularnewline
V(Y[t],d=3,D=2) & 1.37288311688311 & Range & 5.59999999999999 & Trim Var. & 0.740391836734693 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62072&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]0.287830601092896[/C][C]Range[/C][C]2.1[/C][C]Trim Var.[/C][C]0.156955782312925[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]0.064550847457627[/C][C]Range[/C][C]1.3[/C][C]Trim Var.[/C][C]0.0327413273001508[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]0.066206896551724[/C][C]Range[/C][C]1.1[/C][C]Trim Var.[/C][C]0.0404939668174962[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]0.135075620084694[/C][C]Range[/C][C]1.9[/C][C]Trim Var.[/C][C]0.0699660633484162[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]0.064550847457627[/C][C]Range[/C][C]1.3[/C][C]Trim Var.[/C][C]0.0327413273001508[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.066206896551724[/C][C]Range[/C][C]1.1[/C][C]Trim Var.[/C][C]0.0404939668174962[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]0.135075620084694[/C][C]Range[/C][C]1.9[/C][C]Trim Var.[/C][C]0.0699660633484162[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]0.400307017543859[/C][C]Range[/C][C]3[/C][C]Trim Var.[/C][C]0.215796078431372[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]0.066206896551724[/C][C]Range[/C][C]1.1[/C][C]Trim Var.[/C][C]0.0404939668174962[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]0.135075620084694[/C][C]Range[/C][C]1.9[/C][C]Trim Var.[/C][C]0.0699660633484162[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]0.400307017543859[/C][C]Range[/C][C]3[/C][C]Trim Var.[/C][C]0.215796078431372[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]1.37288311688311[/C][C]Range[/C][C]5.59999999999999[/C][C]Trim Var.[/C][C]0.740391836734693[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62072&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62072&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)0.287830601092896Range2.1Trim Var.0.156955782312925
V(Y[t],d=1,D=0)0.064550847457627Range1.3Trim Var.0.0327413273001508
V(Y[t],d=2,D=0)0.066206896551724Range1.1Trim Var.0.0404939668174962
V(Y[t],d=3,D=0)0.135075620084694Range1.9Trim Var.0.0699660633484162
V(Y[t],d=0,D=1)0.064550847457627Range1.3Trim Var.0.0327413273001508
V(Y[t],d=1,D=1)0.066206896551724Range1.1Trim Var.0.0404939668174962
V(Y[t],d=2,D=1)0.135075620084694Range1.9Trim Var.0.0699660633484162
V(Y[t],d=3,D=1)0.400307017543859Range3Trim Var.0.215796078431372
V(Y[t],d=0,D=2)0.066206896551724Range1.1Trim Var.0.0404939668174962
V(Y[t],d=1,D=2)0.135075620084694Range1.9Trim Var.0.0699660633484162
V(Y[t],d=2,D=2)0.400307017543859Range3Trim Var.0.215796078431372
V(Y[t],d=3,D=2)1.37288311688311Range5.59999999999999Trim Var.0.740391836734693


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ;
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')