FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationTue, 06 Dec 2011 16:33:23 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/06/t13232072265mokpk0g4aor2q7.htm/, Retrieved Sun, 28 Apr 2024 23:00:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=151961, Retrieved Sun, 28 Apr 2024 23:00:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact91

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]
- RMP   [(Partial) Autocorrelation Function] [Unemployment] [2010-11-29 09:05:21] [b98453cac15ba1066b407e146608df68]
- R PD    [(Partial) Autocorrelation Function] [WS9 - ACF (d=1)] [2010-12-07 08:39:01] [1f5baf2b24e732d76900bb8178fc04e7]
- RMP       [Spectral Analysis] [CP d=1] [2011-12-06 20:43:55] [19d77e37efa419fdc040c74a96874aff]
- RMP           [Variance Reduction Matrix] [VRM] [2011-12-06 21:33:23] [0f9b7c3b8d01420b2751adc6f98a35df] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2.4
2.4
2.5
2.6
2.4
2.6
2.4
2.3
2.4
2.4
2.4
2.4
2.4
2.4
2.4
2.4
2.5
2.1
2.1
2
2
2
1.9
1.9
2
1.8
1.6
1.3
1.4
1.4
1.5
1.7
1.6
1.5
1.6
1.5
1.1
1.1
1.1
1.4
1.3
1.4
1.3
1.1
1
0.9
0.8
0.8
0.8
0.8
1
1.1
1
0.9
1.1
1.2
1.2
1.4
1.5
1.7
1.9
1.9
1.9
1.7
1.7
2.1
2
2
2.5
2.4
2.5
2.5
2
1.9
2.2
2.7
3.1
2.8
2.6
2.3
2.2
2.2
2
2
2.6
2.5
2.5
2.3
2
1.9
2
2.1
2.1
2.3
2.3
2.3
2.1
2.4
2.5
2.1
1.8
1.9
1.9
2.1
2.2
2
2.2
2
1.9
1.6
1.7
2
2.5
2.4
2.3
2.3
2.1
2.4
2.2
2.4
1.9
2.1
2.1
2.1
2
2.1
2.2
2.2
2.6
2.5
2.3
2.2
2.4
2.3
2.2
2.5
2.5
2.5
2.4
2.3
1.7
1.6
1.9
1.9
1.8
1.8
1.9
1.9
1.9
1.9
1.8
1.7
2.1
2.6
3.1
3.1
3.2
3.3
3.6
3.3
3.7
4
4
3.8
3.6
3.2
2.1
1.6
1.1
1.2
0.6
0.6
0
-0.1
-0.6
-0.2
-0.3
-0.1
0.5
0.9

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\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 & 0 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=151961&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]0 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=151961&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=151961&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 time0 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Variance Reduction Matrix
V(Y[t],d=0,D=0)0.570394475481068Range4.6Trim Var.0.255105590062112
V(Y[t],d=1,D=0)0.0591990458853807Range1.7Trim Var.0.0286399371069182
V(Y[t],d=2,D=0)0.0955881419412175Range1.6Trim Var.0.0560445053616061
V(Y[t],d=3,D=0)0.285167565485362Range2.8Trim Var.0.163403391449725
V(Y[t],d=0,D=1)1.17065297975478Range6.8Trim Var.0.364277163069109
V(Y[t],d=1,D=1)0.172693167881105Range3.3Trim Var.0.081064756031199
V(Y[t],d=2,D=1)0.269243154435926Range2.5Trim Var.0.164417631917632
V(Y[t],d=3,D=1)0.791140428677014Range4.6Trim Var.0.464366787811015
V(Y[t],d=0,D=2)2.60255210918114Range9.6Trim Var.0.936199383350462
V(Y[t],d=1,D=2)0.53396564725597Range5.2Trim Var.0.258239712260658
V(Y[t],d=2,D=2)0.841329258976318Range4.3Trim Var.0.515573207385144
V(Y[t],d=3,D=2)2.43680168558651Range7.9Trim Var.1.45355501089325

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 0.570394475481068 & Range & 4.6 & Trim Var. & 0.255105590062112 \tabularnewline
V(Y[t],d=1,D=0) & 0.0591990458853807 & Range & 1.7 & Trim Var. & 0.0286399371069182 \tabularnewline
V(Y[t],d=2,D=0) & 0.0955881419412175 & Range & 1.6 & Trim Var. & 0.0560445053616061 \tabularnewline
V(Y[t],d=3,D=0) & 0.285167565485362 & Range & 2.8 & Trim Var. & 0.163403391449725 \tabularnewline
V(Y[t],d=0,D=1) & 1.17065297975478 & Range & 6.8 & Trim Var. & 0.364277163069109 \tabularnewline
V(Y[t],d=1,D=1) & 0.172693167881105 & Range & 3.3 & Trim Var. & 0.081064756031199 \tabularnewline
V(Y[t],d=2,D=1) & 0.269243154435926 & Range & 2.5 & Trim Var. & 0.164417631917632 \tabularnewline
V(Y[t],d=3,D=1) & 0.791140428677014 & Range & 4.6 & Trim Var. & 0.464366787811015 \tabularnewline
V(Y[t],d=0,D=2) & 2.60255210918114 & Range & 9.6 & Trim Var. & 0.936199383350462 \tabularnewline
V(Y[t],d=1,D=2) & 0.53396564725597 & Range & 5.2 & Trim Var. & 0.258239712260658 \tabularnewline
V(Y[t],d=2,D=2) & 0.841329258976318 & Range & 4.3 & Trim Var. & 0.515573207385144 \tabularnewline
V(Y[t],d=3,D=2) & 2.43680168558651 & Range & 7.9 & Trim Var. & 1.45355501089325 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=151961&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]0.570394475481068[/C][C]Range[/C][C]4.6[/C][C]Trim Var.[/C][C]0.255105590062112[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]0.0591990458853807[/C][C]Range[/C][C]1.7[/C][C]Trim Var.[/C][C]0.0286399371069182[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]0.0955881419412175[/C][C]Range[/C][C]1.6[/C][C]Trim Var.[/C][C]0.0560445053616061[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]0.285167565485362[/C][C]Range[/C][C]2.8[/C][C]Trim Var.[/C][C]0.163403391449725[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]1.17065297975478[/C][C]Range[/C][C]6.8[/C][C]Trim Var.[/C][C]0.364277163069109[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.172693167881105[/C][C]Range[/C][C]3.3[/C][C]Trim Var.[/C][C]0.081064756031199[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]0.269243154435926[/C][C]Range[/C][C]2.5[/C][C]Trim Var.[/C][C]0.164417631917632[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]0.791140428677014[/C][C]Range[/C][C]4.6[/C][C]Trim Var.[/C][C]0.464366787811015[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]2.60255210918114[/C][C]Range[/C][C]9.6[/C][C]Trim Var.[/C][C]0.936199383350462[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]0.53396564725597[/C][C]Range[/C][C]5.2[/C][C]Trim Var.[/C][C]0.258239712260658[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]0.841329258976318[/C][C]Range[/C][C]4.3[/C][C]Trim Var.[/C][C]0.515573207385144[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]2.43680168558651[/C][C]Range[/C][C]7.9[/C][C]Trim Var.[/C][C]1.45355501089325[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=151961&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=151961&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)0.570394475481068Range4.6Trim Var.0.255105590062112
V(Y[t],d=1,D=0)0.0591990458853807Range1.7Trim Var.0.0286399371069182
V(Y[t],d=2,D=0)0.0955881419412175Range1.6Trim Var.0.0560445053616061
V(Y[t],d=3,D=0)0.285167565485362Range2.8Trim Var.0.163403391449725
V(Y[t],d=0,D=1)1.17065297975478Range6.8Trim Var.0.364277163069109
V(Y[t],d=1,D=1)0.172693167881105Range3.3Trim Var.0.081064756031199
V(Y[t],d=2,D=1)0.269243154435926Range2.5Trim Var.0.164417631917632
V(Y[t],d=3,D=1)0.791140428677014Range4.6Trim Var.0.464366787811015
V(Y[t],d=0,D=2)2.60255210918114Range9.6Trim Var.0.936199383350462
V(Y[t],d=1,D=2)0.53396564725597Range5.2Trim Var.0.258239712260658
V(Y[t],d=2,D=2)0.841329258976318Range4.3Trim Var.0.515573207385144
V(Y[t],d=3,D=2)2.43680168558651Range7.9Trim Var.1.45355501089325


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()