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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, 26 Dec 2010 15:43:49 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/26/t1293378299b066shj5i75x9le.htm/, Retrieved Mon, 06 May 2024 10:59:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=115675, Retrieved Mon, 06 May 2024 10:59:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact117

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] [] [2008-12-08 19:22:39] [d2d412c7f4d35ffbf5ee5ee89db327d4]
-  MP   [Univariate Data Series] [W6_1] [2010-12-14 20:21:12] [7318566ef3ec88988be4d1362d0cf918]
- RMPD      [Variance Reduction Matrix] [Paper_VRM] [2010-12-26 15:43:49] [edf51d809b713abfc4095a7dca74558e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
112.52
112.39
112.24
112.10
109.85
111.89
111.88
111.48
110.98
110.42
107.90
109.46
109.11
109.26
109.99
110.17
110.28
109.13
110.15
109.39
108.45
108.23
107.44
104.86
106.23
105.85
104.95
104.46
104.66
103.05
104.16
104.08
104.20
103.68
103.69
101.29
103.03
102.90
102.68
102.98
103.47
101.72
102.82
102.74
102.38
101.81
101.88
99.60
100.93
100.85
100.93
101.10
101.10
99.31
100.33
99.99
99.82
99.65
99.06
96.92
98.20
98.54
98.71
98.20
98.29
96.67
97.69
97.78
97.44
96.92
96.84
95.05
96.33
96.33
96.16
96.50
96.33
94.71
95.82
95.47
95.82
95.99
95.73
93.77
94.71
94.62
94.79
94.88
94.79
93.43
94.37
94.62
94.45
94.37
94.20
92.66
93.51
93.60
93.60
93.77
93.60
92.41
93.60
93.34
92.92
92.07
91.89
90.27
91.72
91.98
91.81
91.98
91.30
89.93
90.87
90.53
90.27
90.10
89.68
87.89

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=115675&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=115675&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115675&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)43.4018378081232Range24.63Trim Var.33.8893539892696
V(Y[t],d=1,D=0)0.887277211223473Range4.62Trim Var.0.538664627049903
V(Y[t],d=2,D=0)2.46890638852673Range6.69999999999999Trim Var.1.58242484276730
V(Y[t],d=3,D=0)8.13450623342175Range12.8900000000000Trim Var.5.19105782051282
V(Y[t],d=0,D=1)1.30639428002769Range6.51Trim Var.0.541054714445688
V(Y[t],d=1,D=1)0.542479104214423Range6.49999999999999Trim Var.0.121695475923852
V(Y[t],d=2,D=1)1.51491037735849Range11.7300000000000Trim Var.0.244708716540835
V(Y[t],d=3,D=1)5.09829446886446Range19.8400000000000Trim Var.0.654454020570359
V(Y[t],d=0,D=2)3.06617183114035Range10.8000000000000Trim Var.1.21083595075239
V(Y[t],d=1,D=2)0.892761209406495Range6.82999999999997Trim Var.0.36402179271709
V(Y[t],d=2,D=2)1.99695145275681Range10.9200000000000Trim Var.0.74778673264486
V(Y[t],d=3,D=2)6.31318690977092Range18.7200000000000Trim Var.2.16349700264470

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 43.4018378081232 & Range & 24.63 & Trim Var. & 33.8893539892696 \tabularnewline
V(Y[t],d=1,D=0) & 0.887277211223473 & Range & 4.62 & Trim Var. & 0.538664627049903 \tabularnewline
V(Y[t],d=2,D=0) & 2.46890638852673 & Range & 6.69999999999999 & Trim Var. & 1.58242484276730 \tabularnewline
V(Y[t],d=3,D=0) & 8.13450623342175 & Range & 12.8900000000000 & Trim Var. & 5.19105782051282 \tabularnewline
V(Y[t],d=0,D=1) & 1.30639428002769 & Range & 6.51 & Trim Var. & 0.541054714445688 \tabularnewline
V(Y[t],d=1,D=1) & 0.542479104214423 & Range & 6.49999999999999 & Trim Var. & 0.121695475923852 \tabularnewline
V(Y[t],d=2,D=1) & 1.51491037735849 & Range & 11.7300000000000 & Trim Var. & 0.244708716540835 \tabularnewline
V(Y[t],d=3,D=1) & 5.09829446886446 & Range & 19.8400000000000 & Trim Var. & 0.654454020570359 \tabularnewline
V(Y[t],d=0,D=2) & 3.06617183114035 & Range & 10.8000000000000 & Trim Var. & 1.21083595075239 \tabularnewline
V(Y[t],d=1,D=2) & 0.892761209406495 & Range & 6.82999999999997 & Trim Var. & 0.36402179271709 \tabularnewline
V(Y[t],d=2,D=2) & 1.99695145275681 & Range & 10.9200000000000 & Trim Var. & 0.74778673264486 \tabularnewline
V(Y[t],d=3,D=2) & 6.31318690977092 & Range & 18.7200000000000 & Trim Var. & 2.16349700264470 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115675&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]43.4018378081232[/C][C]Range[/C][C]24.63[/C][C]Trim Var.[/C][C]33.8893539892696[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]0.887277211223473[/C][C]Range[/C][C]4.62[/C][C]Trim Var.[/C][C]0.538664627049903[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]2.46890638852673[/C][C]Range[/C][C]6.69999999999999[/C][C]Trim Var.[/C][C]1.58242484276730[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]8.13450623342175[/C][C]Range[/C][C]12.8900000000000[/C][C]Trim Var.[/C][C]5.19105782051282[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]1.30639428002769[/C][C]Range[/C][C]6.51[/C][C]Trim Var.[/C][C]0.541054714445688[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.542479104214423[/C][C]Range[/C][C]6.49999999999999[/C][C]Trim Var.[/C][C]0.121695475923852[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]1.51491037735849[/C][C]Range[/C][C]11.7300000000000[/C][C]Trim Var.[/C][C]0.244708716540835[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]5.09829446886446[/C][C]Range[/C][C]19.8400000000000[/C][C]Trim Var.[/C][C]0.654454020570359[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]3.06617183114035[/C][C]Range[/C][C]10.8000000000000[/C][C]Trim Var.[/C][C]1.21083595075239[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]0.892761209406495[/C][C]Range[/C][C]6.82999999999997[/C][C]Trim Var.[/C][C]0.36402179271709[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]1.99695145275681[/C][C]Range[/C][C]10.9200000000000[/C][C]Trim Var.[/C][C]0.74778673264486[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]6.31318690977092[/C][C]Range[/C][C]18.7200000000000[/C][C]Trim Var.[/C][C]2.16349700264470[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115675&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115675&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)43.4018378081232Range24.63Trim Var.33.8893539892696
V(Y[t],d=1,D=0)0.887277211223473Range4.62Trim Var.0.538664627049903
V(Y[t],d=2,D=0)2.46890638852673Range6.69999999999999Trim Var.1.58242484276730
V(Y[t],d=3,D=0)8.13450623342175Range12.8900000000000Trim Var.5.19105782051282
V(Y[t],d=0,D=1)1.30639428002769Range6.51Trim Var.0.541054714445688
V(Y[t],d=1,D=1)0.542479104214423Range6.49999999999999Trim Var.0.121695475923852
V(Y[t],d=2,D=1)1.51491037735849Range11.7300000000000Trim Var.0.244708716540835
V(Y[t],d=3,D=1)5.09829446886446Range19.8400000000000Trim Var.0.654454020570359
V(Y[t],d=0,D=2)3.06617183114035Range10.8000000000000Trim Var.1.21083595075239
V(Y[t],d=1,D=2)0.892761209406495Range6.82999999999997Trim Var.0.36402179271709
V(Y[t],d=2,D=2)1.99695145275681Range10.9200000000000Trim Var.0.74778673264486
V(Y[t],d=3,D=2)6.31318690977092Range18.7200000000000Trim Var.2.16349700264470


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(myx,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')
bitmap(file='pic0.png')
op <- par(mfrow=c(2,2))
plot(x,type='l',xlab='time',ylab='value',main='d=0, D=0')
plot(diff(x,lag=1,differences=1),type='l',xlab='time',ylab='value',main='d=1, D=0')
plot(diff(x,lag=par1,differences=1),type='l',xlab='time',ylab='value',main='d=0, D=1')
plot(diff(diff(x,lag=1,differences=1),lag=par1,differences=1),type='l',xlab='time',ylab='value',main='d=1, D=1')
par(op)
dev.off()