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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 computationMon, 27 Dec 2010 17:45:25 +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/27/t1293471989dwu6ag051hs204m.htm/, Retrieved Mon, 06 May 2024 11:44:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=116071, Retrieved Mon, 06 May 2024 11:44:29 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact149

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       [Spectral Analysis] [Identifying Integ...] [2009-11-22 12:38:17] [b98453cac15ba1066b407e146608df68]
-    D        [Spectral Analysis] [spectrumanalyse] [2009-11-28 09:48:21] [7773f496f69461f4a67891f0ef752622]
-   PD          [Spectral Analysis] [koffie en thee] [2009-12-16 20:15:20] [7773f496f69461f4a67891f0ef752622]
- RMPD            [Variance Reduction Matrix] [thee] [2009-12-16 20:39:57] [7773f496f69461f4a67891f0ef752622]
-    D              [Variance Reduction Matrix] [Appelen Jonagold ...] [2009-12-17 16:45:59] [7773f496f69461f4a67891f0ef752622]
- R PD                [Variance Reduction Matrix] [Variance reductio...] [2010-12-15 16:28:30] [717f3d787904f94c39256c5c1fc72d4c]
-   P                     [Variance Reduction Matrix] [Peer] [2010-12-27 17:45:25] [039869833c16fe697975601e6b065e0f] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1.3031
1.3241
1.2961
1.2865
1.2305
1.2101
1.2125
1.2350
1.2014
1.1992
1.1791
1.1832
1.2159
1.1922
1.2114
1.2614
1.2812
1.2786
1.2772
1.2815
1.2679
1.2765
1.3247
1.3191
1.3029
1.3234
1.3354
1.3651
1.3453
1.3534
1.3706
1.3638
1.4268
1.4485
1.4635
1.4587
1.4876
1.5189
1.5783
1.5633
1.5554
1.5757
1.5593
1.4660
1.4065
1.2759
1.2705
1.3954
1.2793
1.2694
1.3282
1.3230
1.4135
1.4042
1.4253
1.4322
1.4632
1.4713
1.5016
1.4318

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'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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116071&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116071&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116071&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'George Udny Yule' @ 72.249.76.132






Variance Reduction Matrix
V(Y[t],d=0,D=0)0.0123270277514124Range0.3992Trim Var.0.00936358631726066
V(Y[t],d=1,D=0)0.00181507637054354Range0.2555Trim Var.0.000728310870827287
V(Y[t],d=2,D=0)0.00355614300060497Range0.3713Trim Var.0.00158523710407240
V(Y[t],d=3,D=0)0.0103189210588973Range0.7185Trim Var.0.00399135313725492
V(Y[t],d=0,D=1)0.0205270751595745Range0.493Trim Var.0.0147782079210221
V(Y[t],d=1,D=1)0.00468284344125810Range0.3334Trim Var.0.00215049039024391
V(Y[t],d=2,D=1)0.00678165265700484Range0.4248Trim Var.0.00281529507051283
V(Y[t],d=3,D=1)0.0154801674040404Range0.8033Trim Var.0.00589289260458841
V(Y[t],d=0,D=2)0.0585462128571429Range0.9171Trim Var.0.0418729039415323
V(Y[t],d=1,D=2)0.0142555621008403Range0.6154Trim Var.0.00699413131182795
V(Y[t],d=2,D=2)0.0167029643582888Range0.5587Trim Var.0.00892494998850576
V(Y[t],d=3,D=2)0.0303024848484849Range0.89220Trim Var.0.0148512830541872

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 0.0123270277514124 & Range & 0.3992 & Trim Var. & 0.00936358631726066 \tabularnewline
V(Y[t],d=1,D=0) & 0.00181507637054354 & Range & 0.2555 & Trim Var. & 0.000728310870827287 \tabularnewline
V(Y[t],d=2,D=0) & 0.00355614300060497 & Range & 0.3713 & Trim Var. & 0.00158523710407240 \tabularnewline
V(Y[t],d=3,D=0) & 0.0103189210588973 & Range & 0.7185 & Trim Var. & 0.00399135313725492 \tabularnewline
V(Y[t],d=0,D=1) & 0.0205270751595745 & Range & 0.493 & Trim Var. & 0.0147782079210221 \tabularnewline
V(Y[t],d=1,D=1) & 0.00468284344125810 & Range & 0.3334 & Trim Var. & 0.00215049039024391 \tabularnewline
V(Y[t],d=2,D=1) & 0.00678165265700484 & Range & 0.4248 & Trim Var. & 0.00281529507051283 \tabularnewline
V(Y[t],d=3,D=1) & 0.0154801674040404 & Range & 0.8033 & Trim Var. & 0.00589289260458841 \tabularnewline
V(Y[t],d=0,D=2) & 0.0585462128571429 & Range & 0.9171 & Trim Var. & 0.0418729039415323 \tabularnewline
V(Y[t],d=1,D=2) & 0.0142555621008403 & Range & 0.6154 & Trim Var. & 0.00699413131182795 \tabularnewline
V(Y[t],d=2,D=2) & 0.0167029643582888 & Range & 0.5587 & Trim Var. & 0.00892494998850576 \tabularnewline
V(Y[t],d=3,D=2) & 0.0303024848484849 & Range & 0.89220 & Trim Var. & 0.0148512830541872 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116071&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]0.0123270277514124[/C][C]Range[/C][C]0.3992[/C][C]Trim Var.[/C][C]0.00936358631726066[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]0.00181507637054354[/C][C]Range[/C][C]0.2555[/C][C]Trim Var.[/C][C]0.000728310870827287[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]0.00355614300060497[/C][C]Range[/C][C]0.3713[/C][C]Trim Var.[/C][C]0.00158523710407240[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]0.0103189210588973[/C][C]Range[/C][C]0.7185[/C][C]Trim Var.[/C][C]0.00399135313725492[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]0.0205270751595745[/C][C]Range[/C][C]0.493[/C][C]Trim Var.[/C][C]0.0147782079210221[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.00468284344125810[/C][C]Range[/C][C]0.3334[/C][C]Trim Var.[/C][C]0.00215049039024391[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]0.00678165265700484[/C][C]Range[/C][C]0.4248[/C][C]Trim Var.[/C][C]0.00281529507051283[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]0.0154801674040404[/C][C]Range[/C][C]0.8033[/C][C]Trim Var.[/C][C]0.00589289260458841[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]0.0585462128571429[/C][C]Range[/C][C]0.9171[/C][C]Trim Var.[/C][C]0.0418729039415323[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]0.0142555621008403[/C][C]Range[/C][C]0.6154[/C][C]Trim Var.[/C][C]0.00699413131182795[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]0.0167029643582888[/C][C]Range[/C][C]0.5587[/C][C]Trim Var.[/C][C]0.00892494998850576[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]0.0303024848484849[/C][C]Range[/C][C]0.89220[/C][C]Trim Var.[/C][C]0.0148512830541872[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116071&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116071&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)0.0123270277514124Range0.3992Trim Var.0.00936358631726066
V(Y[t],d=1,D=0)0.00181507637054354Range0.2555Trim Var.0.000728310870827287
V(Y[t],d=2,D=0)0.00355614300060497Range0.3713Trim Var.0.00158523710407240
V(Y[t],d=3,D=0)0.0103189210588973Range0.7185Trim Var.0.00399135313725492
V(Y[t],d=0,D=1)0.0205270751595745Range0.493Trim Var.0.0147782079210221
V(Y[t],d=1,D=1)0.00468284344125810Range0.3334Trim Var.0.00215049039024391
V(Y[t],d=2,D=1)0.00678165265700484Range0.4248Trim Var.0.00281529507051283
V(Y[t],d=3,D=1)0.0154801674040404Range0.8033Trim Var.0.00589289260458841
V(Y[t],d=0,D=2)0.0585462128571429Range0.9171Trim Var.0.0418729039415323
V(Y[t],d=1,D=2)0.0142555621008403Range0.6154Trim Var.0.00699413131182795
V(Y[t],d=2,D=2)0.0167029643582888Range0.5587Trim Var.0.00892494998850576
V(Y[t],d=3,D=2)0.0303024848484849Range0.89220Trim Var.0.0148512830541872


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()