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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 computationSun, 16 Dec 2007 07:32:57 -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/Dec/16/t119781458684twhoobv6dx25g.htm/, Retrieved Thu, 02 May 2024 03:24:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=4186, Retrieved Thu, 02 May 2024 03:24:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsenergieprijzen
Estimated Impact180

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...] [2007-12-16 14:32:57] [0eafefa7b02d47065fceb6c46f54fbf9] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
104,3
103,9
103,9
103,9
108,0
108,0
108,0
108,0
108,0
108,0
108,0
108,0
108,0
108,0
108,0
108,0
108,0
108,0
108,0
108,0
108,0
108,0
108,0
108,0
108,0
108,0
108,0
108,2
112,3
111,3
111,3
115,3
117,2
118,3
118,3
118,3
119,0
120,6
122,6
122,6
127,4
125,9
121,5
118,8
121,6
122,3
122,7
120,8
120,1
120,1
120,1
120,1
128,4
129,8
129,8
128,6
128,6
133,7
130,0
125,9
129,4
129,4
130,6
130,6
130,6
130,8
129,7
125,8
126,0
125,6
125,4
124,7
126,9
129,1

Tables (Output of Computation)





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4186&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=4186&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4186&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 time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Variance Reduction Matrix
V(Y[t],d=0,D=0)84.6600684931507Range29.8Trim Var.70.2868653846154
V(Y[t],d=1,D=0)4.0021499238965Range12.7000000000000Trim Var.1.21690228174603
V(Y[t],d=2,D=0)7.78797339593114Range17.1Trim Var.2.84476190476190
V(Y[t],d=3,D=0)21.5728249496982Range23.6Trim Var.9.39447516641064
V(Y[t],d=0,D=1)29.2753886832364Range23.2Trim Var.19.2548707197764
V(Y[t],d=1,D=1)6.50629508196721Range12.7000000000000Trim Var.2.95783744557329
V(Y[t],d=2,D=1)11.9692542372881Range17.5Trim Var.6.45293151642207
V(Y[t],d=3,D=1)35.1529690239625Range31.1Trim Var.19.4590420899854
V(Y[t],d=0,D=2)94.3036734693878Range34.1Trim Var.69.2449058693245
V(Y[t],d=1,D=2)20.4083248299320Range20.6000000000000Trim Var.9.91930232558138
V(Y[t],d=2,D=2)36.6229609929077Range30.4Trim Var.19.5433739837398
V(Y[t],d=3,D=2)109.699916743756Range50.4999999999999Trim Var.55.6223780487803

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 84.6600684931507 & Range & 29.8 & Trim Var. & 70.2868653846154 \tabularnewline
V(Y[t],d=1,D=0) & 4.0021499238965 & Range & 12.7000000000000 & Trim Var. & 1.21690228174603 \tabularnewline
V(Y[t],d=2,D=0) & 7.78797339593114 & Range & 17.1 & Trim Var. & 2.84476190476190 \tabularnewline
V(Y[t],d=3,D=0) & 21.5728249496982 & Range & 23.6 & Trim Var. & 9.39447516641064 \tabularnewline
V(Y[t],d=0,D=1) & 29.2753886832364 & Range & 23.2 & Trim Var. & 19.2548707197764 \tabularnewline
V(Y[t],d=1,D=1) & 6.50629508196721 & Range & 12.7000000000000 & Trim Var. & 2.95783744557329 \tabularnewline
V(Y[t],d=2,D=1) & 11.9692542372881 & Range & 17.5 & Trim Var. & 6.45293151642207 \tabularnewline
V(Y[t],d=3,D=1) & 35.1529690239625 & Range & 31.1 & Trim Var. & 19.4590420899854 \tabularnewline
V(Y[t],d=0,D=2) & 94.3036734693878 & Range & 34.1 & Trim Var. & 69.2449058693245 \tabularnewline
V(Y[t],d=1,D=2) & 20.4083248299320 & Range & 20.6000000000000 & Trim Var. & 9.91930232558138 \tabularnewline
V(Y[t],d=2,D=2) & 36.6229609929077 & Range & 30.4 & Trim Var. & 19.5433739837398 \tabularnewline
V(Y[t],d=3,D=2) & 109.699916743756 & Range & 50.4999999999999 & Trim Var. & 55.6223780487803 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4186&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]84.6600684931507[/C][C]Range[/C][C]29.8[/C][C]Trim Var.[/C][C]70.2868653846154[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]4.0021499238965[/C][C]Range[/C][C]12.7000000000000[/C][C]Trim Var.[/C][C]1.21690228174603[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]7.78797339593114[/C][C]Range[/C][C]17.1[/C][C]Trim Var.[/C][C]2.84476190476190[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]21.5728249496982[/C][C]Range[/C][C]23.6[/C][C]Trim Var.[/C][C]9.39447516641064[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]29.2753886832364[/C][C]Range[/C][C]23.2[/C][C]Trim Var.[/C][C]19.2548707197764[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]6.50629508196721[/C][C]Range[/C][C]12.7000000000000[/C][C]Trim Var.[/C][C]2.95783744557329[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]11.9692542372881[/C][C]Range[/C][C]17.5[/C][C]Trim Var.[/C][C]6.45293151642207[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]35.1529690239625[/C][C]Range[/C][C]31.1[/C][C]Trim Var.[/C][C]19.4590420899854[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]94.3036734693878[/C][C]Range[/C][C]34.1[/C][C]Trim Var.[/C][C]69.2449058693245[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]20.4083248299320[/C][C]Range[/C][C]20.6000000000000[/C][C]Trim Var.[/C][C]9.91930232558138[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]36.6229609929077[/C][C]Range[/C][C]30.4[/C][C]Trim Var.[/C][C]19.5433739837398[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]109.699916743756[/C][C]Range[/C][C]50.4999999999999[/C][C]Trim Var.[/C][C]55.6223780487803[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=4186&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4186&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)84.6600684931507Range29.8Trim Var.70.2868653846154
V(Y[t],d=1,D=0)4.0021499238965Range12.7000000000000Trim Var.1.21690228174603
V(Y[t],d=2,D=0)7.78797339593114Range17.1Trim Var.2.84476190476190
V(Y[t],d=3,D=0)21.5728249496982Range23.6Trim Var.9.39447516641064
V(Y[t],d=0,D=1)29.2753886832364Range23.2Trim Var.19.2548707197764
V(Y[t],d=1,D=1)6.50629508196721Range12.7000000000000Trim Var.2.95783744557329
V(Y[t],d=2,D=1)11.9692542372881Range17.5Trim Var.6.45293151642207
V(Y[t],d=3,D=1)35.1529690239625Range31.1Trim Var.19.4590420899854
V(Y[t],d=0,D=2)94.3036734693878Range34.1Trim Var.69.2449058693245
V(Y[t],d=1,D=2)20.4083248299320Range20.6000000000000Trim Var.9.91930232558138
V(Y[t],d=2,D=2)36.6229609929077Range30.4Trim Var.19.5433739837398
V(Y[t],d=3,D=2)109.699916743756Range50.4999999999999Trim Var.55.6223780487803


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')