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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 computationTue, 24 Nov 2009 08:46:16 -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/Nov/24/t1259077781criueq6gk0gw1lq.htm/, Retrieved Wed, 06 Dec 2023 07:43:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59131, Retrieved Wed, 06 Dec 2023 07:43:31 +0000
QR Codes:

Original text written by user:Uitleg in Word document
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact202
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] [Bestedingen consu...] [2009-11-24 15:46:16] [8eb8270f5a1cfdf0409dcfcbf10be18b] [Current]
-   PD            [Variance Reduction Matrix] [Workshop 9] [2010-12-10 21:08:50] [74be16979710d4c4e7c6647856088456]
-   PD            [Variance Reduction Matrix] [Workshop 9] [2010-12-10 21:08:50] [1ec36cc0fd92fd0f07d0b885ce2c369b]
- R  D            [Variance Reduction Matrix] [] [2010-12-27 20:53:01] [adca540665f1dd1a5a4406fd7f55bdf4]
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Dataseries X:
96.96
93.11
95.62
98.30
96.38
100.82
99.06
94.03
102.07
99.31
98.64
101.82
99.14
97.63
100.06
101.32
101.49
105.43
105.09
99.48
108.53
104.34
106.10
107.35
103.00
104.50
105.17
104.84
106.18
108.86
107.77
102.74
112.63
106.26
108.86
111.38
106.85
107.86
107.94
111.38
111.29
113.72
111.88
109.87
113.72
111.71
114.81
112.05
111.54
110.87
110.87
115.48
111.63
116.24
113.56
106.01
110.45
107.77
108.61
108.19




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=59131&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=59131&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59131&T=0

As an alternative you can also use a 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)33.8971426836158Range23.13Trim Var.24.7156176100629
V(Y[t],d=1,D=0)13.2845791934541Range17.44Trim Var.7.6724193759071
V(Y[t],d=2,D=0)41.7662255595886Range31.18Trim Var.23.8467288084464
V(Y[t],d=3,D=0)141.062470112782Range56.41Trim Var.83.5151974117647
V(Y[t],d=0,D=1)9.29833882978724Range13.66Trim Var.3.5232406097561
V(Y[t],d=1,D=1)5.38616077705829Range10.4Trim Var.2.60154890243903
V(Y[t],d=2,D=1)16.3327377777778Range19.46Trim Var.9.0785819871795
V(Y[t],d=3,D=1)53.8498518181819Range34.4600000000000Trim Var.27.7085835357625
V(Y[t],d=0,D=2)13.9045101587302Range16.0200000000000Trim Var.7.43723709677419
V(Y[t],d=1,D=2)13.5321843697479Range16.1800000000000Trim Var.7.92512946236558
V(Y[t],d=2,D=2)38.9940435828877Range26.85Trim Var.22.570971954023
V(Y[t],d=3,D=2)122.068700189394Range50.5100000000001Trim Var.60.533125862069

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 33.8971426836158 & Range & 23.13 & Trim Var. & 24.7156176100629 \tabularnewline
V(Y[t],d=1,D=0) & 13.2845791934541 & Range & 17.44 & Trim Var. & 7.6724193759071 \tabularnewline
V(Y[t],d=2,D=0) & 41.7662255595886 & Range & 31.18 & Trim Var. & 23.8467288084464 \tabularnewline
V(Y[t],d=3,D=0) & 141.062470112782 & Range & 56.41 & Trim Var. & 83.5151974117647 \tabularnewline
V(Y[t],d=0,D=1) & 9.29833882978724 & Range & 13.66 & Trim Var. & 3.5232406097561 \tabularnewline
V(Y[t],d=1,D=1) & 5.38616077705829 & Range & 10.4 & Trim Var. & 2.60154890243903 \tabularnewline
V(Y[t],d=2,D=1) & 16.3327377777778 & Range & 19.46 & Trim Var. & 9.0785819871795 \tabularnewline
V(Y[t],d=3,D=1) & 53.8498518181819 & Range & 34.4600000000000 & Trim Var. & 27.7085835357625 \tabularnewline
V(Y[t],d=0,D=2) & 13.9045101587302 & Range & 16.0200000000000 & Trim Var. & 7.43723709677419 \tabularnewline
V(Y[t],d=1,D=2) & 13.5321843697479 & Range & 16.1800000000000 & Trim Var. & 7.92512946236558 \tabularnewline
V(Y[t],d=2,D=2) & 38.9940435828877 & Range & 26.85 & Trim Var. & 22.570971954023 \tabularnewline
V(Y[t],d=3,D=2) & 122.068700189394 & Range & 50.5100000000001 & Trim Var. & 60.533125862069 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59131&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]33.8971426836158[/C][C]Range[/C][C]23.13[/C][C]Trim Var.[/C][C]24.7156176100629[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]13.2845791934541[/C][C]Range[/C][C]17.44[/C][C]Trim Var.[/C][C]7.6724193759071[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]41.7662255595886[/C][C]Range[/C][C]31.18[/C][C]Trim Var.[/C][C]23.8467288084464[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]141.062470112782[/C][C]Range[/C][C]56.41[/C][C]Trim Var.[/C][C]83.5151974117647[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]9.29833882978724[/C][C]Range[/C][C]13.66[/C][C]Trim Var.[/C][C]3.5232406097561[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]5.38616077705829[/C][C]Range[/C][C]10.4[/C][C]Trim Var.[/C][C]2.60154890243903[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]16.3327377777778[/C][C]Range[/C][C]19.46[/C][C]Trim Var.[/C][C]9.0785819871795[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]53.8498518181819[/C][C]Range[/C][C]34.4600000000000[/C][C]Trim Var.[/C][C]27.7085835357625[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]13.9045101587302[/C][C]Range[/C][C]16.0200000000000[/C][C]Trim Var.[/C][C]7.43723709677419[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]13.5321843697479[/C][C]Range[/C][C]16.1800000000000[/C][C]Trim Var.[/C][C]7.92512946236558[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]38.9940435828877[/C][C]Range[/C][C]26.85[/C][C]Trim Var.[/C][C]22.570971954023[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]122.068700189394[/C][C]Range[/C][C]50.5100000000001[/C][C]Trim Var.[/C][C]60.533125862069[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59131&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59131&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Variance Reduction Matrix
V(Y[t],d=0,D=0)33.8971426836158Range23.13Trim Var.24.7156176100629
V(Y[t],d=1,D=0)13.2845791934541Range17.44Trim Var.7.6724193759071
V(Y[t],d=2,D=0)41.7662255595886Range31.18Trim Var.23.8467288084464
V(Y[t],d=3,D=0)141.062470112782Range56.41Trim Var.83.5151974117647
V(Y[t],d=0,D=1)9.29833882978724Range13.66Trim Var.3.5232406097561
V(Y[t],d=1,D=1)5.38616077705829Range10.4Trim Var.2.60154890243903
V(Y[t],d=2,D=1)16.3327377777778Range19.46Trim Var.9.0785819871795
V(Y[t],d=3,D=1)53.8498518181819Range34.4600000000000Trim Var.27.7085835357625
V(Y[t],d=0,D=2)13.9045101587302Range16.0200000000000Trim Var.7.43723709677419
V(Y[t],d=1,D=2)13.5321843697479Range16.1800000000000Trim Var.7.92512946236558
V(Y[t],d=2,D=2)38.9940435828877Range26.85Trim Var.22.570971954023
V(Y[t],d=3,D=2)122.068700189394Range50.5100000000001Trim Var.60.533125862069



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')