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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 computationThu, 17 Dec 2009 02:42:04 -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/17/t1261043424we2tt762yuw5r5p.htm/, Retrieved Tue, 30 Apr 2024 02:29:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=68676, Retrieved Tue, 30 Apr 2024 02:29:41 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact128

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]
-   PD        [(Partial) Autocorrelation Function] [Ws 8 autocorrelat...] [2009-11-27 12:17:11] [12f02da0296cb21dc23d82ae014a8b71]
-   PD          [(Partial) Autocorrelation Function] [Paper Y3 D=d=1] [2009-12-14 10:36:30] [4637f404ac59dfaba4ecf14efa20abbd]
- RMP               [Variance Reduction Matrix] [Paper Y3 variance...] [2009-12-17 09:42:04] [b653746fe14da1ddc21bd75262e8c46b] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
98.2
96.92
99.06
99.65
99.82
99.99
100.33
99.31
101.1
101.1
100.93
100.85
100.93
99.6
101.88
101.81
102.38
102.74
102.82
101.72
103.47
102.98
102.68
102.9
103.03
101.29
103.69
103.68
104.2
104.08
104.16
103.05
104.66
104.46
104.95
105.85
106.23
104.86
107.44
108.23
108.45
109.39
110.15
109.13
110.28
110.17
109.99
109.26
109.11
107.06
109.53
108.92
109.24
109.12
109
107.23
109.49
109.04
109.02
109.23

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=68676&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=68676&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68676&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)14.4128244067797Range13.36Trim Var.11.7935320754717
V(Y[t],d=1,D=0)1.17459053185272Range4.63Trim Var.0.764072714078374
V(Y[t],d=2,D=0)3.46253723532969Range7.6Trim Var.2.36824162895928
V(Y[t],d=3,D=0)11.5533459273183Range14.0200000000000Trim Var.7.82491349019606
V(Y[t],d=0,D=1)3.57862548758865Range7.97999999999999Trim Var.2.13078170731707
V(Y[t],d=1,D=1)0.344572247918592Range2.73999999999997Trim Var.0.173883048780488
V(Y[t],d=2,D=1)0.524199855072455Range3.30999999999995Trim Var.0.280466089743585
V(Y[t],d=3,D=1)1.62752646464643Range6.09999999999995Trim Var.0.842544939271232
V(Y[t],d=0,D=2)12.3195987301587Range12.73Trim Var.8.97769516129033
V(Y[t],d=1,D=2)1.14247932773108Range4.87999999999995Trim Var.0.654398279569893
V(Y[t],d=2,D=2)1.45331524064168Range5.11999999999998Trim Var.0.865342988505733
V(Y[t],d=3,D=2)4.37590643939384Range9.62999999999997Trim Var.2.25406674876840

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 14.4128244067797 & Range & 13.36 & Trim Var. & 11.7935320754717 \tabularnewline
V(Y[t],d=1,D=0) & 1.17459053185272 & Range & 4.63 & Trim Var. & 0.764072714078374 \tabularnewline
V(Y[t],d=2,D=0) & 3.46253723532969 & Range & 7.6 & Trim Var. & 2.36824162895928 \tabularnewline
V(Y[t],d=3,D=0) & 11.5533459273183 & Range & 14.0200000000000 & Trim Var. & 7.82491349019606 \tabularnewline
V(Y[t],d=0,D=1) & 3.57862548758865 & Range & 7.97999999999999 & Trim Var. & 2.13078170731707 \tabularnewline
V(Y[t],d=1,D=1) & 0.344572247918592 & Range & 2.73999999999997 & Trim Var. & 0.173883048780488 \tabularnewline
V(Y[t],d=2,D=1) & 0.524199855072455 & Range & 3.30999999999995 & Trim Var. & 0.280466089743585 \tabularnewline
V(Y[t],d=3,D=1) & 1.62752646464643 & Range & 6.09999999999995 & Trim Var. & 0.842544939271232 \tabularnewline
V(Y[t],d=0,D=2) & 12.3195987301587 & Range & 12.73 & Trim Var. & 8.97769516129033 \tabularnewline
V(Y[t],d=1,D=2) & 1.14247932773108 & Range & 4.87999999999995 & Trim Var. & 0.654398279569893 \tabularnewline
V(Y[t],d=2,D=2) & 1.45331524064168 & Range & 5.11999999999998 & Trim Var. & 0.865342988505733 \tabularnewline
V(Y[t],d=3,D=2) & 4.37590643939384 & Range & 9.62999999999997 & Trim Var. & 2.25406674876840 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68676&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]14.4128244067797[/C][C]Range[/C][C]13.36[/C][C]Trim Var.[/C][C]11.7935320754717[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]1.17459053185272[/C][C]Range[/C][C]4.63[/C][C]Trim Var.[/C][C]0.764072714078374[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]3.46253723532969[/C][C]Range[/C][C]7.6[/C][C]Trim Var.[/C][C]2.36824162895928[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]11.5533459273183[/C][C]Range[/C][C]14.0200000000000[/C][C]Trim Var.[/C][C]7.82491349019606[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]3.57862548758865[/C][C]Range[/C][C]7.97999999999999[/C][C]Trim Var.[/C][C]2.13078170731707[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.344572247918592[/C][C]Range[/C][C]2.73999999999997[/C][C]Trim Var.[/C][C]0.173883048780488[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]0.524199855072455[/C][C]Range[/C][C]3.30999999999995[/C][C]Trim Var.[/C][C]0.280466089743585[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]1.62752646464643[/C][C]Range[/C][C]6.09999999999995[/C][C]Trim Var.[/C][C]0.842544939271232[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]12.3195987301587[/C][C]Range[/C][C]12.73[/C][C]Trim Var.[/C][C]8.97769516129033[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]1.14247932773108[/C][C]Range[/C][C]4.87999999999995[/C][C]Trim Var.[/C][C]0.654398279569893[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]1.45331524064168[/C][C]Range[/C][C]5.11999999999998[/C][C]Trim Var.[/C][C]0.865342988505733[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]4.37590643939384[/C][C]Range[/C][C]9.62999999999997[/C][C]Trim Var.[/C][C]2.25406674876840[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68676&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68676&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)14.4128244067797Range13.36Trim Var.11.7935320754717
V(Y[t],d=1,D=0)1.17459053185272Range4.63Trim Var.0.764072714078374
V(Y[t],d=2,D=0)3.46253723532969Range7.6Trim Var.2.36824162895928
V(Y[t],d=3,D=0)11.5533459273183Range14.0200000000000Trim Var.7.82491349019606
V(Y[t],d=0,D=1)3.57862548758865Range7.97999999999999Trim Var.2.13078170731707
V(Y[t],d=1,D=1)0.344572247918592Range2.73999999999997Trim Var.0.173883048780488
V(Y[t],d=2,D=1)0.524199855072455Range3.30999999999995Trim Var.0.280466089743585
V(Y[t],d=3,D=1)1.62752646464643Range6.09999999999995Trim Var.0.842544939271232
V(Y[t],d=0,D=2)12.3195987301587Range12.73Trim Var.8.97769516129033
V(Y[t],d=1,D=2)1.14247932773108Range4.87999999999995Trim Var.0.654398279569893
V(Y[t],d=2,D=2)1.45331524064168Range5.11999999999998Trim Var.0.865342988505733
V(Y[t],d=3,D=2)4.37590643939384Range9.62999999999997Trim Var.2.25406674876840


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')