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Author's title

Author

*Unverified author*

R Software Module

rwasp_variancereduction.wasp

Title produced by software

Variance Reduction Matrix

Date of computation

Tue, 09 Dec 2008 04:05:49 -0700

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Dec/09/t1228820776r2lgbx843um4n42.htm/, Retrieved Sat, 25 May 2024 11:46:19 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31289, Retrieved Sat, 25 May 2024 11:46:19 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

160

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

F     [Variance Reduction Matrix] [] [2008-12-04 19:38:14] [03c8f0b5f6fe0fafd3d60ad5379ae7bd]
F    D    [Variance Reduction Matrix] [] [2008-12-09 11:05:49] [d41d8cd98f00b204e9800998ecf8427e] [Current]

Feedback Forum

2008-12-13 13:07:27 [Ken Wright] [reply] 
correct,deze calculator gaat trachten de verschillende waarden te zoeken om het best te kunnen differentiëren, dus de beste waarden voor d en D. In de eerste kolom van de geproduceerde tabel zien we de optimale waarden voor d en D. De tweede kolom geeft de bijhorende variantie weer, dus na differentiatie met de gegeven waarden d en D. Om de beste waarden voor d en D te achter halen moeten we kijken naar de rij met de kleinste variantie. . Men moet hier wel oppassen, bij de gewone spreiding wordt de invloed van outliers (=waarden die extreem afwijken van het gemiddelde) mee in acht genomen. Daarom kan men beter gebruikmaken van de trimmed variance, deze houdt namelijk geen rekening met outliers. 

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Dataseries X:

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31289&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31289&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31289&T=0

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Herman Ole Andreas Wold' @ 193.190.124.10:1001

Variance Reduction Matrix
V(Y[t],d=0,D=0)	69923350.7001777	Range	41105	Trim Var.	48309771.461706
V(Y[t],d=1,D=0)	70680430.9174725	Range	49403	Trim Var.	38142321.8475083
V(Y[t],d=2,D=0)	187785404.884321	Range	81668	Trim Var.	104356011.980502
V(Y[t],d=3,D=0)	597235894.665002	Range	144799	Trim Var.	346348798.893044
V(Y[t],d=0,D=1)	23090481.2983507	Range	40060	Trim Var.	11469970.0843455
V(Y[t],d=1,D=1)	32102438.5498144	Range	43012	Trim Var.	14540852.6924500
V(Y[t],d=2,D=1)	94329945.7885974	Range	71954	Trim Var.	38417891.426055
V(Y[t],d=3,D=1)	314788917.908645	Range	137069	Trim Var.	127276226.907288
V(Y[t],d=0,D=2)	67733313.4400198	Range	67070	Trim Var.	32271024.5661930
V(Y[t],d=1,D=2)	97194804.870781	Range	83340	Trim Var.	44403830.2865579
V(Y[t],d=2,D=2)	280117553.906462	Range	132879	Trim Var.	113987160.597213
V(Y[t],d=3,D=2)	934429008.149477	Range	251069	Trim Var.	369303577.611338

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 69923350.7001777 & Range & 41105 & Trim Var. & 48309771.461706 \tabularnewline
V(Y[t],d=1,D=0) & 70680430.9174725 & Range & 49403 & Trim Var. & 38142321.8475083 \tabularnewline
V(Y[t],d=2,D=0) & 187785404.884321 & Range & 81668 & Trim Var. & 104356011.980502 \tabularnewline
V(Y[t],d=3,D=0) & 597235894.665002 & Range & 144799 & Trim Var. & 346348798.893044 \tabularnewline
V(Y[t],d=0,D=1) & 23090481.2983507 & Range & 40060 & Trim Var. & 11469970.0843455 \tabularnewline
V(Y[t],d=1,D=1) & 32102438.5498144 & Range & 43012 & Trim Var. & 14540852.6924500 \tabularnewline
V(Y[t],d=2,D=1) & 94329945.7885974 & Range & 71954 & Trim Var. & 38417891.426055 \tabularnewline
V(Y[t],d=3,D=1) & 314788917.908645 & Range & 137069 & Trim Var. & 127276226.907288 \tabularnewline
V(Y[t],d=0,D=2) & 67733313.4400198 & Range & 67070 & Trim Var. & 32271024.5661930 \tabularnewline
V(Y[t],d=1,D=2) & 97194804.870781 & Range & 83340 & Trim Var. & 44403830.2865579 \tabularnewline
V(Y[t],d=2,D=2) & 280117553.906462 & Range & 132879 & Trim Var. & 113987160.597213 \tabularnewline
V(Y[t],d=3,D=2) & 934429008.149477 & Range & 251069 & Trim Var. & 369303577.611338 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31289&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]69923350.7001777[/C][C]Range[/C][C]41105[/C][C]Trim Var.[/C][C]48309771.461706[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]70680430.9174725[/C][C]Range[/C][C]49403[/C][C]Trim Var.[/C][C]38142321.8475083[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]187785404.884321[/C][C]Range[/C][C]81668[/C][C]Trim Var.[/C][C]104356011.980502[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]597235894.665002[/C][C]Range[/C][C]144799[/C][C]Trim Var.[/C][C]346348798.893044[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]23090481.2983507[/C][C]Range[/C][C]40060[/C][C]Trim Var.[/C][C]11469970.0843455[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]32102438.5498144[/C][C]Range[/C][C]43012[/C][C]Trim Var.[/C][C]14540852.6924500[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]94329945.7885974[/C][C]Range[/C][C]71954[/C][C]Trim Var.[/C][C]38417891.426055[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]314788917.908645[/C][C]Range[/C][C]137069[/C][C]Trim Var.[/C][C]127276226.907288[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]67733313.4400198[/C][C]Range[/C][C]67070[/C][C]Trim Var.[/C][C]32271024.5661930[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]97194804.870781[/C][C]Range[/C][C]83340[/C][C]Trim Var.[/C][C]44403830.2865579[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]280117553.906462[/C][C]Range[/C][C]132879[/C][C]Trim Var.[/C][C]113987160.597213[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]934429008.149477[/C][C]Range[/C][C]251069[/C][C]Trim Var.[/C][C]369303577.611338[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31289&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31289&T=1

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Variance Reduction Matrix
V(Y[t],d=0,D=0)	69923350.7001777	Range	41105	Trim Var.	48309771.461706
V(Y[t],d=1,D=0)	70680430.9174725	Range	49403	Trim Var.	38142321.8475083
V(Y[t],d=2,D=0)	187785404.884321	Range	81668	Trim Var.	104356011.980502
V(Y[t],d=3,D=0)	597235894.665002	Range	144799	Trim Var.	346348798.893044
V(Y[t],d=0,D=1)	23090481.2983507	Range	40060	Trim Var.	11469970.0843455
V(Y[t],d=1,D=1)	32102438.5498144	Range	43012	Trim Var.	14540852.6924500
V(Y[t],d=2,D=1)	94329945.7885974	Range	71954	Trim Var.	38417891.426055
V(Y[t],d=3,D=1)	314788917.908645	Range	137069	Trim Var.	127276226.907288
V(Y[t],d=0,D=2)	67733313.4400198	Range	67070	Trim Var.	32271024.5661930
V(Y[t],d=1,D=2)	97194804.870781	Range	83340	Trim Var.	44403830.2865579
V(Y[t],d=2,D=2)	280117553.906462	Range	132879	Trim Var.	113987160.597213
V(Y[t],d=3,D=2)	934429008.149477	Range	251069	Trim Var.	369303577.611338

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')

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