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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 computationMon, 28 Dec 2009 12:47:48 -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/28/t12620298604plpvq65ygho41i.htm/, Retrieved Sun, 05 May 2024 10:37:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=71044, Retrieved Sun, 05 May 2024 10:37:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact93

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]
- RM D          [Variance Reduction Matrix] [methode 2 g] [2009-12-28 19:47:48] [f47dffd5f5a8c03c3681db4cc9472742] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
110,75
110,64
110,46
110,66
110,48
110,5
110,96
111,17
111,07
111,75
111,45
111,24
111,09
111,29
111,15
110,88
111,22
110,62
110,2
109,49
109,32
108,71
107,85
107,44
106,93
106,19
105,71
105,67
105,7
105,28
105,34
105,58
105,23
105,46
104,92
104,68
104,58
104,32
104,36
104,38
104,25
103,93
103,95
103,6
103,23
103,31
102,82
102,76
102,68
102,37
102,54
102,65
102,63
102,22
102,04
101,85
101,88
101,33
100,8

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=71044&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=71044&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71044&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)12.4785495616598Range10.95Trim Var.10.9202063860668
V(Y[t],d=1,D=0)0.0941887779794315Range1.54000000000001Trim Var.0.0567704374057312
V(Y[t],d=2,D=0)0.158148308270677Range1.76000000000002Trim Var.0.102076705882354
V(Y[t],d=3,D=0)0.498184642857144Range2.92999999999999Trim Var.0.331199224489798
V(Y[t],d=0,D=1)2.71078233117484Range6.25999999999999Trim Var.1.70647804878049
V(Y[t],d=1,D=1)0.213242705314010Range2.24000000000001Trim Var.0.112477948717948
V(Y[t],d=2,D=1)0.292681313131315Range2.23999999999999Trim Var.0.159757624831311
V(Y[t],d=3,D=1)0.888325369978862Range4.27999999999997Trim Var.0.425955334281653
V(Y[t],d=0,D=2)9.3546499159664Range10.35Trim Var.6.9913929032258
V(Y[t],d=1,D=2)0.683062032085566Range3.67Trim Var.0.372811609195403
V(Y[t],d=2,D=2)0.903594507575765Range4.22000000000001Trim Var.0.527447290640397
V(Y[t],d=3,D=2)2.73422580645163Range7.71Trim Var.1.35515132275134

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 12.4785495616598 & Range & 10.95 & Trim Var. & 10.9202063860668 \tabularnewline
V(Y[t],d=1,D=0) & 0.0941887779794315 & Range & 1.54000000000001 & Trim Var. & 0.0567704374057312 \tabularnewline
V(Y[t],d=2,D=0) & 0.158148308270677 & Range & 1.76000000000002 & Trim Var. & 0.102076705882354 \tabularnewline
V(Y[t],d=3,D=0) & 0.498184642857144 & Range & 2.92999999999999 & Trim Var. & 0.331199224489798 \tabularnewline
V(Y[t],d=0,D=1) & 2.71078233117484 & Range & 6.25999999999999 & Trim Var. & 1.70647804878049 \tabularnewline
V(Y[t],d=1,D=1) & 0.213242705314010 & Range & 2.24000000000001 & Trim Var. & 0.112477948717948 \tabularnewline
V(Y[t],d=2,D=1) & 0.292681313131315 & Range & 2.23999999999999 & Trim Var. & 0.159757624831311 \tabularnewline
V(Y[t],d=3,D=1) & 0.888325369978862 & Range & 4.27999999999997 & Trim Var. & 0.425955334281653 \tabularnewline
V(Y[t],d=0,D=2) & 9.3546499159664 & Range & 10.35 & Trim Var. & 6.9913929032258 \tabularnewline
V(Y[t],d=1,D=2) & 0.683062032085566 & Range & 3.67 & Trim Var. & 0.372811609195403 \tabularnewline
V(Y[t],d=2,D=2) & 0.903594507575765 & Range & 4.22000000000001 & Trim Var. & 0.527447290640397 \tabularnewline
V(Y[t],d=3,D=2) & 2.73422580645163 & Range & 7.71 & Trim Var. & 1.35515132275134 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71044&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]12.4785495616598[/C][C]Range[/C][C]10.95[/C][C]Trim Var.[/C][C]10.9202063860668[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]0.0941887779794315[/C][C]Range[/C][C]1.54000000000001[/C][C]Trim Var.[/C][C]0.0567704374057312[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]0.158148308270677[/C][C]Range[/C][C]1.76000000000002[/C][C]Trim Var.[/C][C]0.102076705882354[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]0.498184642857144[/C][C]Range[/C][C]2.92999999999999[/C][C]Trim Var.[/C][C]0.331199224489798[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]2.71078233117484[/C][C]Range[/C][C]6.25999999999999[/C][C]Trim Var.[/C][C]1.70647804878049[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.213242705314010[/C][C]Range[/C][C]2.24000000000001[/C][C]Trim Var.[/C][C]0.112477948717948[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]0.292681313131315[/C][C]Range[/C][C]2.23999999999999[/C][C]Trim Var.[/C][C]0.159757624831311[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]0.888325369978862[/C][C]Range[/C][C]4.27999999999997[/C][C]Trim Var.[/C][C]0.425955334281653[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]9.3546499159664[/C][C]Range[/C][C]10.35[/C][C]Trim Var.[/C][C]6.9913929032258[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]0.683062032085566[/C][C]Range[/C][C]3.67[/C][C]Trim Var.[/C][C]0.372811609195403[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]0.903594507575765[/C][C]Range[/C][C]4.22000000000001[/C][C]Trim Var.[/C][C]0.527447290640397[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]2.73422580645163[/C][C]Range[/C][C]7.71[/C][C]Trim Var.[/C][C]1.35515132275134[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71044&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71044&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)12.4785495616598Range10.95Trim Var.10.9202063860668
V(Y[t],d=1,D=0)0.0941887779794315Range1.54000000000001Trim Var.0.0567704374057312
V(Y[t],d=2,D=0)0.158148308270677Range1.76000000000002Trim Var.0.102076705882354
V(Y[t],d=3,D=0)0.498184642857144Range2.92999999999999Trim Var.0.331199224489798
V(Y[t],d=0,D=1)2.71078233117484Range6.25999999999999Trim Var.1.70647804878049
V(Y[t],d=1,D=1)0.213242705314010Range2.24000000000001Trim Var.0.112477948717948
V(Y[t],d=2,D=1)0.292681313131315Range2.23999999999999Trim Var.0.159757624831311
V(Y[t],d=3,D=1)0.888325369978862Range4.27999999999997Trim Var.0.425955334281653
V(Y[t],d=0,D=2)9.3546499159664Range10.35Trim Var.6.9913929032258
V(Y[t],d=1,D=2)0.683062032085566Range3.67Trim Var.0.372811609195403
V(Y[t],d=2,D=2)0.903594507575765Range4.22000000000001Trim Var.0.527447290640397
V(Y[t],d=3,D=2)2.73422580645163Range7.71Trim Var.1.35515132275134


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
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')