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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 computationWed, 10 Dec 2008 11:11:05 -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/10/t1228932687gimqschxws9zw29.htm/, Retrieved Sun, 19 May 2024 05:38:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=32054, Retrieved Sun, 19 May 2024 05:38:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact230

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
F RMPD  [Variance Reduction Matrix] [] [2008-11-30 18:13:06] [b745fd448f60064800b631a75a630267]
F RM D    [Standard Deviation-Mean Plot] [SMP Q1] [2008-12-07 13:12:10] [e5d91604aae608e98a8ea24759233f66]
F RM        [Variance Reduction Matrix] [VRM Q1] [2008-12-07 13:13:31] [e5d91604aae608e98a8ea24759233f66]
F RMP         [(Partial) Autocorrelation Function] [ACF Q2] [2008-12-07 13:20:49] [e5d91604aae608e98a8ea24759233f66]
F RMP           [ARIMA Backward Selection] [ARMA Q5] [2008-12-07 13:46:58] [e5d91604aae608e98a8ea24759233f66]
- RMPD              [Variance Reduction Matrix] [VRM werkloosheid] [2008-12-10 18:11:05] [55ca0ca4a201c9689dcf5fae352c92eb] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
9.4
9.4
9.5
9.5
9.4
9.4
9.3
9.4
9.4
9.2
9.1
9.1
9.1
9.1
9
8.9
8.8
8.7
8.4
8.3
8.2
7.9
7.8
7.7
7.3
7.2
7.1
6.9
6.8
6.7
6.8
6.9
6.7
6.8
6.8
6.7
6.3
6.2
6.2
6.5
6.5
6.4
6.2
6.2
6.3
7.5
7.4
7.4
7.4
7.4
7.4
7.2
7.2
7.1
7.5
7.4
7.5
8
8.1
8.1
8.1
8.1
8.1
7.9
7.9
8
8.1
8.1
8.1
8.6
8.6
8.6
8.4
8.4
8.4
7.7
7.8
7.9
8.7
8.8
8.8
8.5
8.5
8.5
8.4
8.5
8.5
8.3
8.4
8.4
8.5
8.4
8.4
8.5
8.5
8.5
8.5
8.5
8.5
8.3
8.3
8.3
8.3
8.2
8.2
8.1
8
7.8
7.9
7.8
7.7
7.8
7.7
7.6
7.3
7.3
7.1
7.1
7.1
7

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'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 & 0 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32054&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32054&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32054&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'George Udny Yule' @ 72.249.76.132






Variance Reduction Matrix
V(Y[t],d=0,D=0)0.723686274509804Range3.3Trim Var.0.485653189577718
V(Y[t],d=1,D=0)0.0414542088021649Range1.9Trim Var.0.00791374663072775
V(Y[t],d=2,D=0)0.0759821816601477Range2.4Trim Var.0.0243809523809523
V(Y[t],d=3,D=0)0.225514294134984Range3.9Trim Var.0.0745301883129487
V(Y[t],d=0,D=1)0.677185012114919Range3.3Trim Var.0.448648026315789
V(Y[t],d=1,D=1)0.063657203315112Range1.9Trim Var.0.0169583619309082
V(Y[t],d=2,D=1)0.118570530098832Range2.1Trim Var.0.0577316403568976
V(Y[t],d=3,D=1)0.350188644688644Range3.6Trim Var.0.165326086956521
V(Y[t],d=0,D=2)0.84396052631579Range3.8Trim Var.0.571158686730506
V(Y[t],d=1,D=2)0.192972004479283Range3Trim Var.0.0678151260504201
V(Y[t],d=2,D=2)0.372239762068176Range3.6Trim Var.0.206143144004589
V(Y[t],d=3,D=2)1.10912575970079Range6.1Trim Var.0.57912136350279

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 0.723686274509804 & Range & 3.3 & Trim Var. & 0.485653189577718 \tabularnewline
V(Y[t],d=1,D=0) & 0.0414542088021649 & Range & 1.9 & Trim Var. & 0.00791374663072775 \tabularnewline
V(Y[t],d=2,D=0) & 0.0759821816601477 & Range & 2.4 & Trim Var. & 0.0243809523809523 \tabularnewline
V(Y[t],d=3,D=0) & 0.225514294134984 & Range & 3.9 & Trim Var. & 0.0745301883129487 \tabularnewline
V(Y[t],d=0,D=1) & 0.677185012114919 & Range & 3.3 & Trim Var. & 0.448648026315789 \tabularnewline
V(Y[t],d=1,D=1) & 0.063657203315112 & Range & 1.9 & Trim Var. & 0.0169583619309082 \tabularnewline
V(Y[t],d=2,D=1) & 0.118570530098832 & Range & 2.1 & Trim Var. & 0.0577316403568976 \tabularnewline
V(Y[t],d=3,D=1) & 0.350188644688644 & Range & 3.6 & Trim Var. & 0.165326086956521 \tabularnewline
V(Y[t],d=0,D=2) & 0.84396052631579 & Range & 3.8 & Trim Var. & 0.571158686730506 \tabularnewline
V(Y[t],d=1,D=2) & 0.192972004479283 & Range & 3 & Trim Var. & 0.0678151260504201 \tabularnewline
V(Y[t],d=2,D=2) & 0.372239762068176 & Range & 3.6 & Trim Var. & 0.206143144004589 \tabularnewline
V(Y[t],d=3,D=2) & 1.10912575970079 & Range & 6.1 & Trim Var. & 0.57912136350279 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32054&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]0.723686274509804[/C][C]Range[/C][C]3.3[/C][C]Trim Var.[/C][C]0.485653189577718[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]0.0414542088021649[/C][C]Range[/C][C]1.9[/C][C]Trim Var.[/C][C]0.00791374663072775[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]0.0759821816601477[/C][C]Range[/C][C]2.4[/C][C]Trim Var.[/C][C]0.0243809523809523[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]0.225514294134984[/C][C]Range[/C][C]3.9[/C][C]Trim Var.[/C][C]0.0745301883129487[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]0.677185012114919[/C][C]Range[/C][C]3.3[/C][C]Trim Var.[/C][C]0.448648026315789[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.063657203315112[/C][C]Range[/C][C]1.9[/C][C]Trim Var.[/C][C]0.0169583619309082[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]0.118570530098832[/C][C]Range[/C][C]2.1[/C][C]Trim Var.[/C][C]0.0577316403568976[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]0.350188644688644[/C][C]Range[/C][C]3.6[/C][C]Trim Var.[/C][C]0.165326086956521[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]0.84396052631579[/C][C]Range[/C][C]3.8[/C][C]Trim Var.[/C][C]0.571158686730506[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]0.192972004479283[/C][C]Range[/C][C]3[/C][C]Trim Var.[/C][C]0.0678151260504201[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]0.372239762068176[/C][C]Range[/C][C]3.6[/C][C]Trim Var.[/C][C]0.206143144004589[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]1.10912575970079[/C][C]Range[/C][C]6.1[/C][C]Trim Var.[/C][C]0.57912136350279[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32054&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32054&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)0.723686274509804Range3.3Trim Var.0.485653189577718
V(Y[t],d=1,D=0)0.0414542088021649Range1.9Trim Var.0.00791374663072775
V(Y[t],d=2,D=0)0.0759821816601477Range2.4Trim Var.0.0243809523809523
V(Y[t],d=3,D=0)0.225514294134984Range3.9Trim Var.0.0745301883129487
V(Y[t],d=0,D=1)0.677185012114919Range3.3Trim Var.0.448648026315789
V(Y[t],d=1,D=1)0.063657203315112Range1.9Trim Var.0.0169583619309082
V(Y[t],d=2,D=1)0.118570530098832Range2.1Trim Var.0.0577316403568976
V(Y[t],d=3,D=1)0.350188644688644Range3.6Trim Var.0.165326086956521
V(Y[t],d=0,D=2)0.84396052631579Range3.8Trim Var.0.571158686730506
V(Y[t],d=1,D=2)0.192972004479283Range3Trim Var.0.0678151260504201
V(Y[t],d=2,D=2)0.372239762068176Range3.6Trim Var.0.206143144004589
V(Y[t],d=3,D=2)1.10912575970079Range6.1Trim Var.0.57912136350279


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')