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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 computationSun, 07 Dec 2008 11:02:35 -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/2008/Dec/07/t1228673001l9ttlf35051q9t2.htm/, Retrieved Sun, 19 May 2024 08:46:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=30201, Retrieved Sun, 19 May 2024 08:46:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact185

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMPD  [Standard Deviation-Mean Plot] [S1] [2008-12-07 17:37:06] [a0d819c22534897f04a2f0b92f1eb36a]
-    D    [Standard Deviation-Mean Plot] [S1] [2008-12-07 17:58:18] [a0d819c22534897f04a2f0b92f1eb36a]
- RM          [Variance Reduction Matrix] [s2] [2008-12-07 18:02:35] [5f3e73ccf1ddc75508eed47fa51813d3] [Current]
- RMP           [(Partial) Autocorrelation Function] [S2 ACF] [2008-12-07 18:10:24] [a0d819c22534897f04a2f0b92f1eb36a]
-   P             [(Partial) Autocorrelation Function] [s2] [2008-12-07 18:12:59] [a0d819c22534897f04a2f0b92f1eb36a]
-   P               [(Partial) Autocorrelation Function] [s2 ACF] [2008-12-07 18:25:03] [a0d819c22534897f04a2f0b92f1eb36a]
-                     [(Partial) Autocorrelation Function] [s2 acf d1D1] [2008-12-07 18:26:56] [a0d819c22534897f04a2f0b92f1eb36a]
- RM                    [Spectral Analysis] [S2 SA - d0 D0 L1] [2008-12-07 18:29:54] [a0d819c22534897f04a2f0b92f1eb36a]
-                         [Spectral Analysis] [s2 SA d1D1 L1] [2008-12-07 18:32:14] [a0d819c22534897f04a2f0b92f1eb36a]
-                           [Spectral Analysis] [s3] [2008-12-07 18:39:13] [a0d819c22534897f04a2f0b92f1eb36a]
-                             [Spectral Analysis] [s3 sa] [2008-12-07 18:42:05] [a0d819c22534897f04a2f0b92f1eb36a]
- RM                            [(Partial) Autocorrelation Function] [s4] [2008-12-07 18:48:27] [a0d819c22534897f04a2f0b92f1eb36a]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
137
136
133
126
120
114
116
153
162
161
149
139
135
130
127
122
117
112
113
149
157
157
147
137
132
125
123
117
114
111
112
144
150
149
134
123
116
117
111
105
102
95
93
124
130
124
115
106
105
105
101
95
93
84
87
116
120
117
109
105

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time7 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 7 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30201&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]7 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30201&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30201&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 time7 seconds
R Server'George Udny Yule' @ 72.249.76.132






Variance Reduction Matrix
V(Y[t],d=0,D=0)362.575141242938Range78Trim Var.225.221719457014
V(Y[t],d=1,D=0)129.493863237873Range52Trim Var.60.8476052249637
V(Y[t],d=2,D=0)180.646400483969Range63Trim Var.88.2926093514329
V(Y[t],d=3,D=0)436.095864661654Range92Trim Var.202.289387755102
V(Y[t],d=0,D=1)35.7442375886525Range24Trim Var.23.6196283391405
V(Y[t],d=1,D=1)8.28214616096207Range13Trim Var.3.50568990042674
V(Y[t],d=2,D=1)17.5386473429952Range23Trim Var.7.1224358974359
V(Y[t],d=3,D=1)56.7727272727273Range38Trim Var.25.2199730094467
V(Y[t],d=0,D=2)88.5301587301587Range36Trim Var.61.2086693548387
V(Y[t],d=1,D=2)22.3747899159664Range20Trim Var.13.7784946236559
V(Y[t],d=2,D=2)58.2112299465241Range32Trim Var.32.9896551724138
V(Y[t],d=3,D=2)197.329545454545Range58Trim Var.89.1384615384615

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 362.575141242938 & Range & 78 & Trim Var. & 225.221719457014 \tabularnewline
V(Y[t],d=1,D=0) & 129.493863237873 & Range & 52 & Trim Var. & 60.8476052249637 \tabularnewline
V(Y[t],d=2,D=0) & 180.646400483969 & Range & 63 & Trim Var. & 88.2926093514329 \tabularnewline
V(Y[t],d=3,D=0) & 436.095864661654 & Range & 92 & Trim Var. & 202.289387755102 \tabularnewline
V(Y[t],d=0,D=1) & 35.7442375886525 & Range & 24 & Trim Var. & 23.6196283391405 \tabularnewline
V(Y[t],d=1,D=1) & 8.28214616096207 & Range & 13 & Trim Var. & 3.50568990042674 \tabularnewline
V(Y[t],d=2,D=1) & 17.5386473429952 & Range & 23 & Trim Var. & 7.1224358974359 \tabularnewline
V(Y[t],d=3,D=1) & 56.7727272727273 & Range & 38 & Trim Var. & 25.2199730094467 \tabularnewline
V(Y[t],d=0,D=2) & 88.5301587301587 & Range & 36 & Trim Var. & 61.2086693548387 \tabularnewline
V(Y[t],d=1,D=2) & 22.3747899159664 & Range & 20 & Trim Var. & 13.7784946236559 \tabularnewline
V(Y[t],d=2,D=2) & 58.2112299465241 & Range & 32 & Trim Var. & 32.9896551724138 \tabularnewline
V(Y[t],d=3,D=2) & 197.329545454545 & Range & 58 & Trim Var. & 89.1384615384615 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30201&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]362.575141242938[/C][C]Range[/C][C]78[/C][C]Trim Var.[/C][C]225.221719457014[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]129.493863237873[/C][C]Range[/C][C]52[/C][C]Trim Var.[/C][C]60.8476052249637[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]180.646400483969[/C][C]Range[/C][C]63[/C][C]Trim Var.[/C][C]88.2926093514329[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]436.095864661654[/C][C]Range[/C][C]92[/C][C]Trim Var.[/C][C]202.289387755102[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]35.7442375886525[/C][C]Range[/C][C]24[/C][C]Trim Var.[/C][C]23.6196283391405[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]8.28214616096207[/C][C]Range[/C][C]13[/C][C]Trim Var.[/C][C]3.50568990042674[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]17.5386473429952[/C][C]Range[/C][C]23[/C][C]Trim Var.[/C][C]7.1224358974359[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]56.7727272727273[/C][C]Range[/C][C]38[/C][C]Trim Var.[/C][C]25.2199730094467[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]88.5301587301587[/C][C]Range[/C][C]36[/C][C]Trim Var.[/C][C]61.2086693548387[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]22.3747899159664[/C][C]Range[/C][C]20[/C][C]Trim Var.[/C][C]13.7784946236559[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]58.2112299465241[/C][C]Range[/C][C]32[/C][C]Trim Var.[/C][C]32.9896551724138[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]197.329545454545[/C][C]Range[/C][C]58[/C][C]Trim Var.[/C][C]89.1384615384615[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30201&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30201&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)362.575141242938Range78Trim Var.225.221719457014
V(Y[t],d=1,D=0)129.493863237873Range52Trim Var.60.8476052249637
V(Y[t],d=2,D=0)180.646400483969Range63Trim Var.88.2926093514329
V(Y[t],d=3,D=0)436.095864661654Range92Trim Var.202.289387755102
V(Y[t],d=0,D=1)35.7442375886525Range24Trim Var.23.6196283391405
V(Y[t],d=1,D=1)8.28214616096207Range13Trim Var.3.50568990042674
V(Y[t],d=2,D=1)17.5386473429952Range23Trim Var.7.1224358974359
V(Y[t],d=3,D=1)56.7727272727273Range38Trim Var.25.2199730094467
V(Y[t],d=0,D=2)88.5301587301587Range36Trim Var.61.2086693548387
V(Y[t],d=1,D=2)22.3747899159664Range20Trim Var.13.7784946236559
V(Y[t],d=2,D=2)58.2112299465241Range32Trim Var.32.9896551724138
V(Y[t],d=3,D=2)197.329545454545Range58Trim Var.89.1384615384615


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')