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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_variancereduction.wasp
Title produced by softwareVariance Reduction Matrix
Date of computationMon, 08 Dec 2008 12:28:43 -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/08/t1228764662d4rf04d3gna7xbg.htm/, Retrieved Thu, 16 May 2024 14:14:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=30819, Retrieved Thu, 16 May 2024 14:14:30 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact188

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Variance Reduction Matrix] [q2 VRM] [2008-12-08 19:28:43] [4940af498c7c54f3992f17142bd40069] [Current]
Feedback Forum
2008-12-15 17:58:04 [Nathalie Boden] [reply] 
V(Y[t],d=1,D=0) 240077.809039548 Range 3015 Trim Var. 121998.786862334

Het klopt inderdaad dat bij Y(t), d=1 en D=0 de laagste variantie is terug te vinden. Dit is ook bij de getrimde variantie.
2008-12-15 18:01:43 [Philippe Versluys] [reply] 
ACF en de Cumulative Periodogram worden hier niet geananlyseerd. De VRM is de minder betrouwbaar dan de ACf dus is het ook belangrijkl dat we deze maken en gaan analyseren, want we kunnen andere resultaten bekomen dan bij de VRM.
2008-12-15 18:07:40 [Philippe Versluys] [reply] 
Is inderdaad die met de kleinste varaintie die je moet nemen.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
10511
10812
10738
10171
9721
9897
9828
9924
10371
10846
10413
10709
10662
10570
10297
10635
10872
10296
10383
10431
10574
10653
10805
10872
10625
10407
10463
10556
10646
10702
11353
11346
11451
11964
12574
13031
13812
14544
14931
14886
16005
17064
15168
16050
15839
15137
14954
15648
15305
15579
16348
15928
16171
15937
15713
15594
15683
16438
17032
17696
17745

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=30819&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=30819&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30819&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)6965897.35245902Range8024Trim Var.5726035.11393324
V(Y[t],d=1,D=0)240077.809039548Range3015Trim Var.121998.786862334
V(Y[t],d=2,D=0)527220.683810637Range5733Trim Var.180724.078374456
V(Y[t],d=3,D=0)1612616.78765880Range9604Trim Var.506782.393288084
V(Y[t],d=0,D=1)3075789.73639456Range7489Trim Var.1982504.5393134
V(Y[t],d=1,D=1)612529.751329787Range4219Trim Var.318141.881533101
V(Y[t],d=2,D=1)1353198.21369103Range6986Trim Var.453465.495121951
V(Y[t],d=3,D=1)4148923.10917874Range12624Trim Var.1151819.35833333
V(Y[t],d=0,D=2)10024914.3558559Range13445Trim Var.6577138.19507576
V(Y[t],d=1,D=2)2114970.48492063Range7330Trim Var.1102143.95866935
V(Y[t],d=2,D=2)4565840.16302521Range12624Trim Var.1564944.34623656
V(Y[t],d=3,D=2)13927993.4581105Range21239Trim Var.4865467.8954023

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 6965897.35245902 & Range & 8024 & Trim Var. & 5726035.11393324 \tabularnewline
V(Y[t],d=1,D=0) & 240077.809039548 & Range & 3015 & Trim Var. & 121998.786862334 \tabularnewline
V(Y[t],d=2,D=0) & 527220.683810637 & Range & 5733 & Trim Var. & 180724.078374456 \tabularnewline
V(Y[t],d=3,D=0) & 1612616.78765880 & Range & 9604 & Trim Var. & 506782.393288084 \tabularnewline
V(Y[t],d=0,D=1) & 3075789.73639456 & Range & 7489 & Trim Var. & 1982504.5393134 \tabularnewline
V(Y[t],d=1,D=1) & 612529.751329787 & Range & 4219 & Trim Var. & 318141.881533101 \tabularnewline
V(Y[t],d=2,D=1) & 1353198.21369103 & Range & 6986 & Trim Var. & 453465.495121951 \tabularnewline
V(Y[t],d=3,D=1) & 4148923.10917874 & Range & 12624 & Trim Var. & 1151819.35833333 \tabularnewline
V(Y[t],d=0,D=2) & 10024914.3558559 & Range & 13445 & Trim Var. & 6577138.19507576 \tabularnewline
V(Y[t],d=1,D=2) & 2114970.48492063 & Range & 7330 & Trim Var. & 1102143.95866935 \tabularnewline
V(Y[t],d=2,D=2) & 4565840.16302521 & Range & 12624 & Trim Var. & 1564944.34623656 \tabularnewline
V(Y[t],d=3,D=2) & 13927993.4581105 & Range & 21239 & Trim Var. & 4865467.8954023 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30819&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]6965897.35245902[/C][C]Range[/C][C]8024[/C][C]Trim Var.[/C][C]5726035.11393324[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]240077.809039548[/C][C]Range[/C][C]3015[/C][C]Trim Var.[/C][C]121998.786862334[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]527220.683810637[/C][C]Range[/C][C]5733[/C][C]Trim Var.[/C][C]180724.078374456[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]1612616.78765880[/C][C]Range[/C][C]9604[/C][C]Trim Var.[/C][C]506782.393288084[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]3075789.73639456[/C][C]Range[/C][C]7489[/C][C]Trim Var.[/C][C]1982504.5393134[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]612529.751329787[/C][C]Range[/C][C]4219[/C][C]Trim Var.[/C][C]318141.881533101[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]1353198.21369103[/C][C]Range[/C][C]6986[/C][C]Trim Var.[/C][C]453465.495121951[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]4148923.10917874[/C][C]Range[/C][C]12624[/C][C]Trim Var.[/C][C]1151819.35833333[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]10024914.3558559[/C][C]Range[/C][C]13445[/C][C]Trim Var.[/C][C]6577138.19507576[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]2114970.48492063[/C][C]Range[/C][C]7330[/C][C]Trim Var.[/C][C]1102143.95866935[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]4565840.16302521[/C][C]Range[/C][C]12624[/C][C]Trim Var.[/C][C]1564944.34623656[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]13927993.4581105[/C][C]Range[/C][C]21239[/C][C]Trim Var.[/C][C]4865467.8954023[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30819&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30819&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)6965897.35245902Range8024Trim Var.5726035.11393324
V(Y[t],d=1,D=0)240077.809039548Range3015Trim Var.121998.786862334
V(Y[t],d=2,D=0)527220.683810637Range5733Trim Var.180724.078374456
V(Y[t],d=3,D=0)1612616.78765880Range9604Trim Var.506782.393288084
V(Y[t],d=0,D=1)3075789.73639456Range7489Trim Var.1982504.5393134
V(Y[t],d=1,D=1)612529.751329787Range4219Trim Var.318141.881533101
V(Y[t],d=2,D=1)1353198.21369103Range6986Trim Var.453465.495121951
V(Y[t],d=3,D=1)4148923.10917874Range12624Trim Var.1151819.35833333
V(Y[t],d=0,D=2)10024914.3558559Range13445Trim Var.6577138.19507576
V(Y[t],d=1,D=2)2114970.48492063Range7330Trim Var.1102143.95866935
V(Y[t],d=2,D=2)4565840.16302521Range12624Trim Var.1564944.34623656
V(Y[t],d=3,D=2)13927993.4581105Range21239Trim Var.4865467.8954023


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')