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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 computationWed, 21 Nov 2007 13:10:07 -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/2007/Nov/21/t1195675371op6bhk69b6bn9sg.htm/, Retrieved Tue, 07 May 2024 07:29:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=5881, Retrieved Tue, 07 May 2024 07:29:50 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsvariance reduction matrix, groep 4, paper, voeding
Estimated Impact183

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Variance Reduction Matrix] [Variance reductio...] [2007-11-21 20:10:07] [bd7b8d7754bcf95ad80b21f541dc6b78] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
88,95
88,81
88,90
90,15
90,92
90,78
90,81
89,46
89,22
88,89
89,41
89,59
90,25
90,20
90,27
90,71
91,18
90,66
89,72
88,72
88,91
89,15
89,15
89,08
89,28
89,47
89,53
90,72
90,91
91,38
91,49
90,90
90,93
90,57
91,28
90,83
91,50
91,58
92,49
94,16
95,46
95,80
95,32
95,41
95,35
95,68
95,59
94,96
96,92
96,06
96,59
96,67
97,27
96,38
96,47
96,05
96,76
96,51
96,55
95,97
97,00
97,46
97,90
98,42
98,54
99,00
98,94
99,02
100,07
98,72
98,73
98,04
99,08
99,22
99,57
100,44
100,84
100,75
100,49
99,98
99,96
99,76
100,11
99,79
100,29
101,12
102,65
102,71
103,39
102,80
102,07
102,15
101,21
101,27
101,86
101,65
101,94
102,62
102,71
103,39
104,51
104,09
104,29
104,57
105,39
105,15
106,13
105,46
106,47
106,62
106,52
108,04
107,15
107,32
107,76
107,26
107,89

Tables (Output of Computation)





Summary of compuational 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 compuational 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=5881&T=0

[TABLE]
[ROW][C]Summary of compuational 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=5881&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=5881&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 compuational 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)33.7420031830239Range19.32Trim Var.27.3540116666667
V(Y[t],d=1,D=0)0.390997871064469Range3.31000000000002Trim Var.0.222524709689702
V(Y[t],d=2,D=0)0.85270302059497Range5.41000000000003Trim Var.0.496547515705315
V(Y[t],d=3,D=0)2.77789464368888Range9.62000000000003Trim Var.1.62803234323434
V(Y[t],d=0,D=1)2.2375647985348Range6.51Trim Var.1.49951157082749
V(Y[t],d=1,D=1)0.474484988797613Range3.77000000000002Trim Var.0.278101325848067
V(Y[t],d=2,D=1)1.12111998857797Range5.45Trim Var.0.677038876678885
V(Y[t],d=3,D=1)3.72662174335084Range9.33000000000001Trim Var.2.52438852684147
V(Y[t],d=0,D=2)4.93601220196353Range10.1600000000000Trim Var.3.44380279165442
V(Y[t],d=1,D=2)1.33271336598185Range5.30000000000004Trim Var.0.830470099367667
V(Y[t],d=2,D=2)2.95564153846157Range7.78000000000002Trim Var.1.93390188271607
V(Y[t],d=3,D=2)9.73039377028724Range13.3800000000000Trim Var.6.73338930379753

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 33.7420031830239 & Range & 19.32 & Trim Var. & 27.3540116666667 \tabularnewline
V(Y[t],d=1,D=0) & 0.390997871064469 & Range & 3.31000000000002 & Trim Var. & 0.222524709689702 \tabularnewline
V(Y[t],d=2,D=0) & 0.85270302059497 & Range & 5.41000000000003 & Trim Var. & 0.496547515705315 \tabularnewline
V(Y[t],d=3,D=0) & 2.77789464368888 & Range & 9.62000000000003 & Trim Var. & 1.62803234323434 \tabularnewline
V(Y[t],d=0,D=1) & 2.2375647985348 & Range & 6.51 & Trim Var. & 1.49951157082749 \tabularnewline
V(Y[t],d=1,D=1) & 0.474484988797613 & Range & 3.77000000000002 & Trim Var. & 0.278101325848067 \tabularnewline
V(Y[t],d=2,D=1) & 1.12111998857797 & Range & 5.45 & Trim Var. & 0.677038876678885 \tabularnewline
V(Y[t],d=3,D=1) & 3.72662174335084 & Range & 9.33000000000001 & Trim Var. & 2.52438852684147 \tabularnewline
V(Y[t],d=0,D=2) & 4.93601220196353 & Range & 10.1600000000000 & Trim Var. & 3.44380279165442 \tabularnewline
V(Y[t],d=1,D=2) & 1.33271336598185 & Range & 5.30000000000004 & Trim Var. & 0.830470099367667 \tabularnewline
V(Y[t],d=2,D=2) & 2.95564153846157 & Range & 7.78000000000002 & Trim Var. & 1.93390188271607 \tabularnewline
V(Y[t],d=3,D=2) & 9.73039377028724 & Range & 13.3800000000000 & Trim Var. & 6.73338930379753 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=5881&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]33.7420031830239[/C][C]Range[/C][C]19.32[/C][C]Trim Var.[/C][C]27.3540116666667[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]0.390997871064469[/C][C]Range[/C][C]3.31000000000002[/C][C]Trim Var.[/C][C]0.222524709689702[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]0.85270302059497[/C][C]Range[/C][C]5.41000000000003[/C][C]Trim Var.[/C][C]0.496547515705315[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]2.77789464368888[/C][C]Range[/C][C]9.62000000000003[/C][C]Trim Var.[/C][C]1.62803234323434[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]2.2375647985348[/C][C]Range[/C][C]6.51[/C][C]Trim Var.[/C][C]1.49951157082749[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.474484988797613[/C][C]Range[/C][C]3.77000000000002[/C][C]Trim Var.[/C][C]0.278101325848067[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]1.12111998857797[/C][C]Range[/C][C]5.45[/C][C]Trim Var.[/C][C]0.677038876678885[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]3.72662174335084[/C][C]Range[/C][C]9.33000000000001[/C][C]Trim Var.[/C][C]2.52438852684147[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]4.93601220196353[/C][C]Range[/C][C]10.1600000000000[/C][C]Trim Var.[/C][C]3.44380279165442[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]1.33271336598185[/C][C]Range[/C][C]5.30000000000004[/C][C]Trim Var.[/C][C]0.830470099367667[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]2.95564153846157[/C][C]Range[/C][C]7.78000000000002[/C][C]Trim Var.[/C][C]1.93390188271607[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]9.73039377028724[/C][C]Range[/C][C]13.3800000000000[/C][C]Trim Var.[/C][C]6.73338930379753[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=5881&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=5881&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)33.7420031830239Range19.32Trim Var.27.3540116666667
V(Y[t],d=1,D=0)0.390997871064469Range3.31000000000002Trim Var.0.222524709689702
V(Y[t],d=2,D=0)0.85270302059497Range5.41000000000003Trim Var.0.496547515705315
V(Y[t],d=3,D=0)2.77789464368888Range9.62000000000003Trim Var.1.62803234323434
V(Y[t],d=0,D=1)2.2375647985348Range6.51Trim Var.1.49951157082749
V(Y[t],d=1,D=1)0.474484988797613Range3.77000000000002Trim Var.0.278101325848067
V(Y[t],d=2,D=1)1.12111998857797Range5.45Trim Var.0.677038876678885
V(Y[t],d=3,D=1)3.72662174335084Range9.33000000000001Trim Var.2.52438852684147
V(Y[t],d=0,D=2)4.93601220196353Range10.1600000000000Trim Var.3.44380279165442
V(Y[t],d=1,D=2)1.33271336598185Range5.30000000000004Trim Var.0.830470099367667
V(Y[t],d=2,D=2)2.95564153846157Range7.78000000000002Trim Var.1.93390188271607
V(Y[t],d=3,D=2)9.73039377028724Range13.3800000000000Trim Var.6.73338930379753


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')