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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, 10 Dec 2009 10:19:22 -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/10/t1260465593v7v4dkf6l6rrni4.htm/, Retrieved Sat, 20 Apr 2024 05:50:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=65621, Retrieved Sat, 20 Apr 2024 05:50:51 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact114

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       [Variance Reduction Matrix] [Identifying Integ...] [2009-11-22 12:29:54] [b98453cac15ba1066b407e146608df68]
- R  D        [Variance Reduction Matrix] [workshop 8] [2009-11-26 18:51:39] [3d8acb8ffdb376c5fec19e610f8198c2]
-    D            [Variance Reduction Matrix] [verbetering] [2009-12-10 17:19:22] [5edea6bc5a9a9483633d9320282a2734] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
102.86
102.55
102.28
102.26
102.57
103.08
102.76
102.51
102.87
103.14
103.12
103.16
102.48
102.57
102.88
102.63
102.38
101.69
101.96
102.19
101.87
101.6
101.63
101.22
101.21
101.49
101.64
101.66
101.77
101.82
101.78
101.28
101.29
101.37
101.12
101.51
102.24
102.94
103.09
103.46
103.64
104.39
104.15
105.21
105.8
105.91
105.39
105.46
104.72
103.14
102.63
102.32
101.93
100.62
100.6
99.63
98.9
98.32
99.22
98.81

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65621&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]1 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=65621&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65621&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Variance Reduction Matrix
V(Y[t],d=0,D=0)2.53353152542373Range7.59Trim Var.1.40767044025157
V(Y[t],d=1,D=0)0.249905026300408Range2.63999999999999Trim Var.0.133929245283018
V(Y[t],d=2,D=0)0.359533817301873Range2.79000000000002Trim Var.0.222237707390646
V(Y[t],d=3,D=0)1.01449511278195Range5.08Trim Var.0.542294588235289
V(Y[t],d=0,D=1)8.08751489361701Range12.13Trim Var.4.31367921022067
V(Y[t],d=1,D=1)0.687640333024973Range3.83999999999999Trim Var.0.337117439024387
V(Y[t],d=2,D=1)0.988519227053131Range4.52999999999996Trim Var.0.530835641025635
V(Y[t],d=3,D=1)2.83356040404038Range8.29999999999995Trim Var.1.33192564102563
V(Y[t],d=0,D=2)23.8586053968254Range17.22Trim Var.16.9921442540322
V(Y[t],d=1,D=2)1.68056084033612Range5.87999999999997Trim Var.0.948705806451606
V(Y[t],d=2,D=2)2.49834019607841Range7.18999999999996Trim Var.1.45937574712643
V(Y[t],d=3,D=2)7.34253124999994Range12.8899999999999Trim Var.3.73442857142855

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 2.53353152542373 & Range & 7.59 & Trim Var. & 1.40767044025157 \tabularnewline
V(Y[t],d=1,D=0) & 0.249905026300408 & Range & 2.63999999999999 & Trim Var. & 0.133929245283018 \tabularnewline
V(Y[t],d=2,D=0) & 0.359533817301873 & Range & 2.79000000000002 & Trim Var. & 0.222237707390646 \tabularnewline
V(Y[t],d=3,D=0) & 1.01449511278195 & Range & 5.08 & Trim Var. & 0.542294588235289 \tabularnewline
V(Y[t],d=0,D=1) & 8.08751489361701 & Range & 12.13 & Trim Var. & 4.31367921022067 \tabularnewline
V(Y[t],d=1,D=1) & 0.687640333024973 & Range & 3.83999999999999 & Trim Var. & 0.337117439024387 \tabularnewline
V(Y[t],d=2,D=1) & 0.988519227053131 & Range & 4.52999999999996 & Trim Var. & 0.530835641025635 \tabularnewline
V(Y[t],d=3,D=1) & 2.83356040404038 & Range & 8.29999999999995 & Trim Var. & 1.33192564102563 \tabularnewline
V(Y[t],d=0,D=2) & 23.8586053968254 & Range & 17.22 & Trim Var. & 16.9921442540322 \tabularnewline
V(Y[t],d=1,D=2) & 1.68056084033612 & Range & 5.87999999999997 & Trim Var. & 0.948705806451606 \tabularnewline
V(Y[t],d=2,D=2) & 2.49834019607841 & Range & 7.18999999999996 & Trim Var. & 1.45937574712643 \tabularnewline
V(Y[t],d=3,D=2) & 7.34253124999994 & Range & 12.8899999999999 & Trim Var. & 3.73442857142855 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65621&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]2.53353152542373[/C][C]Range[/C][C]7.59[/C][C]Trim Var.[/C][C]1.40767044025157[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]0.249905026300408[/C][C]Range[/C][C]2.63999999999999[/C][C]Trim Var.[/C][C]0.133929245283018[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]0.359533817301873[/C][C]Range[/C][C]2.79000000000002[/C][C]Trim Var.[/C][C]0.222237707390646[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]1.01449511278195[/C][C]Range[/C][C]5.08[/C][C]Trim Var.[/C][C]0.542294588235289[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]8.08751489361701[/C][C]Range[/C][C]12.13[/C][C]Trim Var.[/C][C]4.31367921022067[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.687640333024973[/C][C]Range[/C][C]3.83999999999999[/C][C]Trim Var.[/C][C]0.337117439024387[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]0.988519227053131[/C][C]Range[/C][C]4.52999999999996[/C][C]Trim Var.[/C][C]0.530835641025635[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]2.83356040404038[/C][C]Range[/C][C]8.29999999999995[/C][C]Trim Var.[/C][C]1.33192564102563[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]23.8586053968254[/C][C]Range[/C][C]17.22[/C][C]Trim Var.[/C][C]16.9921442540322[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]1.68056084033612[/C][C]Range[/C][C]5.87999999999997[/C][C]Trim Var.[/C][C]0.948705806451606[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]2.49834019607841[/C][C]Range[/C][C]7.18999999999996[/C][C]Trim Var.[/C][C]1.45937574712643[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]7.34253124999994[/C][C]Range[/C][C]12.8899999999999[/C][C]Trim Var.[/C][C]3.73442857142855[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65621&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65621&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)2.53353152542373Range7.59Trim Var.1.40767044025157
V(Y[t],d=1,D=0)0.249905026300408Range2.63999999999999Trim Var.0.133929245283018
V(Y[t],d=2,D=0)0.359533817301873Range2.79000000000002Trim Var.0.222237707390646
V(Y[t],d=3,D=0)1.01449511278195Range5.08Trim Var.0.542294588235289
V(Y[t],d=0,D=1)8.08751489361701Range12.13Trim Var.4.31367921022067
V(Y[t],d=1,D=1)0.687640333024973Range3.83999999999999Trim Var.0.337117439024387
V(Y[t],d=2,D=1)0.988519227053131Range4.52999999999996Trim Var.0.530835641025635
V(Y[t],d=3,D=1)2.83356040404038Range8.29999999999995Trim Var.1.33192564102563
V(Y[t],d=0,D=2)23.8586053968254Range17.22Trim Var.16.9921442540322
V(Y[t],d=1,D=2)1.68056084033612Range5.87999999999997Trim Var.0.948705806451606
V(Y[t],d=2,D=2)2.49834019607841Range7.18999999999996Trim Var.1.45937574712643
V(Y[t],d=3,D=2)7.34253124999994Range12.8899999999999Trim Var.3.73442857142855


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')