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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 computationSat, 13 Dec 2008 06:47:47 -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/13/t12291761359b61indno7tntel.htm/, Retrieved Fri, 17 May 2024 01:41:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=33087, Retrieved Fri, 17 May 2024 01:41:25 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact198

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [ACF d=0 D=0 voor Xt] [2008-12-13 09:26:24] [b1bd16d1f47bfe13feacf1c27a0abba5]
-   PD  [(Partial) Autocorrelation Function] [ACF d=0 D=1] [2008-12-13 09:29:39] [b1bd16d1f47bfe13feacf1c27a0abba5]
-   PD    [(Partial) Autocorrelation Function] [step 1 ACF d=0 D=0] [2008-12-13 13:32:41] [b1bd16d1f47bfe13feacf1c27a0abba5]
-           [(Partial) Autocorrelation Function] [step 1 ACF d=1 D=0] [2008-12-13 13:35:54] [b1bd16d1f47bfe13feacf1c27a0abba5]
-             [(Partial) Autocorrelation Function] [step 1 ACF d=1 D=1] [2008-12-13 13:38:15] [b1bd16d1f47bfe13feacf1c27a0abba5]
-               [(Partial) Autocorrelation Function] [step 1 ACF d=1 D=2] [2008-12-13 13:42:02] [b1bd16d1f47bfe13feacf1c27a0abba5]
- RM                [Variance Reduction Matrix] [step 1 VRM] [2008-12-13 13:47:47] [e7b1048c2c3a353441b9143db4404b91] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
6.4
6.8
7.5
7.5
7.6
7.6
7.4
7.3
7.1
6.9
6.8
7.5
7.6
7.8
8
8.1
8.2
8.3
8.2
8
7.9
7.6
7.6
8.2
8.3
8.4
8.4
8.4
8.6
8.9
8.8
8.3
7.5
7.2
7.5
8.8
9.3
9.3
8.7
8.2
8.3
8.5
8.6
8.6
8.2
8.1
8
8.6
8.7
8.8
8.5
8.4
8.5
8.7
8.7
8.6
8.5
8.3
8.1
8.2
8.1
8.1
7.9
7.9
7.9
8
8
7.9
8
7.7
7.2
7.5
7.3
7
7
7
7.2
7.3
7.1
6.8
6.6
6.2
6.2
6.8

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'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=33087&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=33087&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33087&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'Gwilym Jenkins' @ 72.249.127.135






Variance Reduction Matrix
V(Y[t],d=0,D=0)0.480761617900172Range3.1Trim Var.0.25975983436853
V(Y[t],d=1,D=0)0.0970496620628857Range2.1Trim Var.0.0343661971830986
V(Y[t],d=2,D=0)0.119993977717555Range1.8Trim Var.0.0577743271221532
V(Y[t],d=3,D=0)0.261361111111111Range2.8Trim Var.0.113923541247485
V(Y[t],d=0,D=1)0.453503521126761Range2.7Trim Var.0.339660218253968
V(Y[t],d=1,D=1)0.0757022132796781Range1.40000000000000Trim Var.0.0328220338983051
V(Y[t],d=2,D=1)0.0850207039337476Range1.30000000000000Trim Var.0.0555711263881545
V(Y[t],d=3,D=1)0.173086104006820Range1.90000000000000Trim Var.0.105989071038252
V(Y[t],d=0,D=2)0.30490395480226Range2.9Trim Var.0.152329462989840
V(Y[t],d=1,D=2)0.197685563997662Range2.50000000000000Trim Var.0.103715529753265
V(Y[t],d=2,D=2)0.214035087719299Range1.90000000000000Trim Var.0.143514328808447
V(Y[t],d=3,D=2)0.407781954887219Range3Trim Var.0.235058823529412

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 0.480761617900172 & Range & 3.1 & Trim Var. & 0.25975983436853 \tabularnewline
V(Y[t],d=1,D=0) & 0.0970496620628857 & Range & 2.1 & Trim Var. & 0.0343661971830986 \tabularnewline
V(Y[t],d=2,D=0) & 0.119993977717555 & Range & 1.8 & Trim Var. & 0.0577743271221532 \tabularnewline
V(Y[t],d=3,D=0) & 0.261361111111111 & Range & 2.8 & Trim Var. & 0.113923541247485 \tabularnewline
V(Y[t],d=0,D=1) & 0.453503521126761 & Range & 2.7 & Trim Var. & 0.339660218253968 \tabularnewline
V(Y[t],d=1,D=1) & 0.0757022132796781 & Range & 1.40000000000000 & Trim Var. & 0.0328220338983051 \tabularnewline
V(Y[t],d=2,D=1) & 0.0850207039337476 & Range & 1.30000000000000 & Trim Var. & 0.0555711263881545 \tabularnewline
V(Y[t],d=3,D=1) & 0.173086104006820 & Range & 1.90000000000000 & Trim Var. & 0.105989071038252 \tabularnewline
V(Y[t],d=0,D=2) & 0.30490395480226 & Range & 2.9 & Trim Var. & 0.152329462989840 \tabularnewline
V(Y[t],d=1,D=2) & 0.197685563997662 & Range & 2.50000000000000 & Trim Var. & 0.103715529753265 \tabularnewline
V(Y[t],d=2,D=2) & 0.214035087719299 & Range & 1.90000000000000 & Trim Var. & 0.143514328808447 \tabularnewline
V(Y[t],d=3,D=2) & 0.407781954887219 & Range & 3 & Trim Var. & 0.235058823529412 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33087&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]0.480761617900172[/C][C]Range[/C][C]3.1[/C][C]Trim Var.[/C][C]0.25975983436853[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]0.0970496620628857[/C][C]Range[/C][C]2.1[/C][C]Trim Var.[/C][C]0.0343661971830986[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]0.119993977717555[/C][C]Range[/C][C]1.8[/C][C]Trim Var.[/C][C]0.0577743271221532[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]0.261361111111111[/C][C]Range[/C][C]2.8[/C][C]Trim Var.[/C][C]0.113923541247485[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]0.453503521126761[/C][C]Range[/C][C]2.7[/C][C]Trim Var.[/C][C]0.339660218253968[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.0757022132796781[/C][C]Range[/C][C]1.40000000000000[/C][C]Trim Var.[/C][C]0.0328220338983051[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]0.0850207039337476[/C][C]Range[/C][C]1.30000000000000[/C][C]Trim Var.[/C][C]0.0555711263881545[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]0.173086104006820[/C][C]Range[/C][C]1.90000000000000[/C][C]Trim Var.[/C][C]0.105989071038252[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]0.30490395480226[/C][C]Range[/C][C]2.9[/C][C]Trim Var.[/C][C]0.152329462989840[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]0.197685563997662[/C][C]Range[/C][C]2.50000000000000[/C][C]Trim Var.[/C][C]0.103715529753265[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]0.214035087719299[/C][C]Range[/C][C]1.90000000000000[/C][C]Trim Var.[/C][C]0.143514328808447[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]0.407781954887219[/C][C]Range[/C][C]3[/C][C]Trim Var.[/C][C]0.235058823529412[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33087&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33087&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)0.480761617900172Range3.1Trim Var.0.25975983436853
V(Y[t],d=1,D=0)0.0970496620628857Range2.1Trim Var.0.0343661971830986
V(Y[t],d=2,D=0)0.119993977717555Range1.8Trim Var.0.0577743271221532
V(Y[t],d=3,D=0)0.261361111111111Range2.8Trim Var.0.113923541247485
V(Y[t],d=0,D=1)0.453503521126761Range2.7Trim Var.0.339660218253968
V(Y[t],d=1,D=1)0.0757022132796781Range1.40000000000000Trim Var.0.0328220338983051
V(Y[t],d=2,D=1)0.0850207039337476Range1.30000000000000Trim Var.0.0555711263881545
V(Y[t],d=3,D=1)0.173086104006820Range1.90000000000000Trim Var.0.105989071038252
V(Y[t],d=0,D=2)0.30490395480226Range2.9Trim Var.0.152329462989840
V(Y[t],d=1,D=2)0.197685563997662Range2.50000000000000Trim Var.0.103715529753265
V(Y[t],d=2,D=2)0.214035087719299Range1.90000000000000Trim Var.0.143514328808447
V(Y[t],d=3,D=2)0.407781954887219Range3Trim Var.0.235058823529412


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 0 ; par3 = 2 ; par4 = 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')