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R Software Module

rwasp_variancereduction.wasp

Title produced by software

Variance Reduction Matrix

Date of computation

Wed, 03 Dec 2008 08:07:18 -0700

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Dec/03/t1228316902uvet89uzkr7znqi.htm/, Retrieved Fri, 19 Apr 2024 03:40:13 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28720, Retrieved Fri, 19 Apr 2024 03:40:13 +0000

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No (this computation is public)

User-defined keywords

Estimated Impact

306

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]
F RMP     [Variance Reduction Matrix] [Taak 10 stap 2 VRM] [2008-12-03 15:07:18] [286e96bd53289970f8e5f25a93fb50b3] [Current]
F    D      [Variance Reduction Matrix] [Taak 10 Stap 2 RV...] [2008-12-04 18:18:25] [819b576fab25b35cfda70f80599828ec] 
-   P         [Variance Reduction Matrix] [Identification an...] [2008-12-08 19:19:34] [79c17183721a40a589db5f9f561947d8] 
F           [Variance Reduction Matrix] [Identification an...] [2008-12-08 19:00:45] [79c17183721a40a589db5f9f561947d8] 
-           [Variance Reduction Matrix] [STEP 2] [2008-12-12 14:58:49] [b85eb1eb4b13b870c6e7ebbba3e34fcc] 
- RMP       [(Partial) Autocorrelation Function] [step 2, d=0 D=0] [2008-12-12 15:01:37] [be21b8e1cbf510e3982bb38b934d7c10] 

Feedback Forum

2008-12-13 14:45:57 [An De Koninck] [reply] 
Correct opgelost.
2008-12-14 09:42:01 [Kristof Van Esbroeck] [reply] 
Student maakt juiste berekening. 
Voorts staat de Seasonal period correct op 12 en trekt student juiste conclusie. 
 
We noteren de kleinste waarde 795.483036989776 waar d = 1 en D = 1, dit wil zeggen dat we één maal gewoon en één maal seizonaal moeten differentiëren om de datareeks stationair te maken. 
 
 
2008-12-14 10:50:50 [Jeroen Michel] [reply] 
Ook hier valt weinig op aan te merken. De student geeft de juiste output weer door gebruik te maken van de juiste module. De student genereerd een correcte output en maakt een correcte bijbehorende analyse.
2008-12-14 12:16:58 [Kevin Neelen] [reply] 
De student heeft hier gebruik gemaakt van de juiste methode om deze vraagstelling op te lossen, namelijk de Variance Reduction Matrix. 
 
De seasonal period werd ingesteld op 12. 
 
We kunnen hier concluderen dat de laagste variantie hier bij d = 1 en D = 1 ligt. Ook de trimmed variance ligt hier het laagst. 
 
De getrokken conclusie van de student klopt dus. 
  2008-12-15 20:57:56 [Nilay Erdogdu] [reply] 
ik ben het eens met de uitleg van Kevin Neelen.
2008-12-14 13:04:30 [Matthieu Blondeau] [reply] 
Dit is correct, men moet de laagste waarde kiezen om de juiste parameters voor d en D te vinden.
2008-12-14 13:34:49 [Ilknur Günes] [reply] 
de variantie is hier het laagst als d = 1 en D = 1, maw de oplossing is correct.
2008-12-14 16:59:09 [Mehmet Yilmaz] [reply] 
Correct.
2008-12-15 10:31:51 [Jef Keersmaekers] [reply] 
Correct de student heeft de laagste variantie gevonden voor d=1 en D=1, ook het trimmed mean zit in deze variantie
2008-12-15 17:58:19 [Steffi Van Isveldt] [reply] 
Zeer juiste berekening met correct getrokken conclusies. Door de juiste module te gebruiken kan je de laagste variantie zoeken
2008-12-15 19:16:51 [Michael Van Spaandonck] [reply] 
Seasonal period werd terecht ingesteld op 12. 
Deze VRM vertelt ons dat de laagste variantie ligt bij d = 1 en D = 1, wat betekent dat er 1 maal saisonaal en 1 maal niet-saisonaal gedifferentieerd moet worden. Ook de trimmed variance ligt hier het laagst.

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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	1 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=28720&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=28720&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28720&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	1 seconds
R Server	'George Udny Yule' @ 72.249.76.132

Variance Reduction Matrix
V(Y[t],d=0,D=0)	24040.7319917109	Range	708.9	Trim Var.	14891.1423067379
V(Y[t],d=1,D=0)	1855.27831616522	Range	306.2	Trim Var.	1019.21726473461
V(Y[t],d=2,D=0)	3601.51571083278	Range	388.2	Trim Var.	1764.07169175190
V(Y[t],d=3,D=0)	10155.4683153647	Range	595.5	Trim Var.	5250.86267655406
V(Y[t],d=0,D=1)	10061.5318845559	Range	585.7	Trim Var.	5798.12009737033
V(Y[t],d=1,D=1)	795.483036989776	Range	221.9	Trim Var.	451.063415764475
V(Y[t],d=2,D=1)	1251.20020977106	Range	223.4	Trim Var.	751.938251968809
V(Y[t],d=3,D=1)	3933.17493248985	Range	389.7	Trim Var.	2351.74535475078
V(Y[t],d=0,D=2)	23022.65043915	Range	819	Trim Var.	13637.4877562041
V(Y[t],d=1,D=2)	2352.87163598807	Range	333.6	Trim Var.	1332.90434353283
V(Y[t],d=2,D=2)	3506.43060400436	Range	407	Trim Var.	2059.39114521349
V(Y[t],d=3,D=2)	10920.6579647792	Range	659.1	Trim Var.	6490.07402051023

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 24040.7319917109 & Range & 708.9 & Trim Var. & 14891.1423067379 \tabularnewline
V(Y[t],d=1,D=0) & 1855.27831616522 & Range & 306.2 & Trim Var. & 1019.21726473461 \tabularnewline
V(Y[t],d=2,D=0) & 3601.51571083278 & Range & 388.2 & Trim Var. & 1764.07169175190 \tabularnewline
V(Y[t],d=3,D=0) & 10155.4683153647 & Range & 595.5 & Trim Var. & 5250.86267655406 \tabularnewline
V(Y[t],d=0,D=1) & 10061.5318845559 & Range & 585.7 & Trim Var. & 5798.12009737033 \tabularnewline
V(Y[t],d=1,D=1) & 795.483036989776 & Range & 221.9 & Trim Var. & 451.063415764475 \tabularnewline
V(Y[t],d=2,D=1) & 1251.20020977106 & Range & 223.4 & Trim Var. & 751.938251968809 \tabularnewline
V(Y[t],d=3,D=1) & 3933.17493248985 & Range & 389.7 & Trim Var. & 2351.74535475078 \tabularnewline
V(Y[t],d=0,D=2) & 23022.65043915 & Range & 819 & Trim Var. & 13637.4877562041 \tabularnewline
V(Y[t],d=1,D=2) & 2352.87163598807 & Range & 333.6 & Trim Var. & 1332.90434353283 \tabularnewline
V(Y[t],d=2,D=2) & 3506.43060400436 & Range & 407 & Trim Var. & 2059.39114521349 \tabularnewline
V(Y[t],d=3,D=2) & 10920.6579647792 & Range & 659.1 & Trim Var. & 6490.07402051023 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28720&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]24040.7319917109[/C][C]Range[/C][C]708.9[/C][C]Trim Var.[/C][C]14891.1423067379[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]1855.27831616522[/C][C]Range[/C][C]306.2[/C][C]Trim Var.[/C][C]1019.21726473461[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]3601.51571083278[/C][C]Range[/C][C]388.2[/C][C]Trim Var.[/C][C]1764.07169175190[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]10155.4683153647[/C][C]Range[/C][C]595.5[/C][C]Trim Var.[/C][C]5250.86267655406[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]10061.5318845559[/C][C]Range[/C][C]585.7[/C][C]Trim Var.[/C][C]5798.12009737033[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]795.483036989776[/C][C]Range[/C][C]221.9[/C][C]Trim Var.[/C][C]451.063415764475[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]1251.20020977106[/C][C]Range[/C][C]223.4[/C][C]Trim Var.[/C][C]751.938251968809[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]3933.17493248985[/C][C]Range[/C][C]389.7[/C][C]Trim Var.[/C][C]2351.74535475078[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]23022.65043915[/C][C]Range[/C][C]819[/C][C]Trim Var.[/C][C]13637.4877562041[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]2352.87163598807[/C][C]Range[/C][C]333.6[/C][C]Trim Var.[/C][C]1332.90434353283[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]3506.43060400436[/C][C]Range[/C][C]407[/C][C]Trim Var.[/C][C]2059.39114521349[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]10920.6579647792[/C][C]Range[/C][C]659.1[/C][C]Trim Var.[/C][C]6490.07402051023[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28720&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28720&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)	24040.7319917109	Range	708.9	Trim Var.	14891.1423067379
V(Y[t],d=1,D=0)	1855.27831616522	Range	306.2	Trim Var.	1019.21726473461
V(Y[t],d=2,D=0)	3601.51571083278	Range	388.2	Trim Var.	1764.07169175190
V(Y[t],d=3,D=0)	10155.4683153647	Range	595.5	Trim Var.	5250.86267655406
V(Y[t],d=0,D=1)	10061.5318845559	Range	585.7	Trim Var.	5798.12009737033
V(Y[t],d=1,D=1)	795.483036989776	Range	221.9	Trim Var.	451.063415764475
V(Y[t],d=2,D=1)	1251.20020977106	Range	223.4	Trim Var.	751.938251968809
V(Y[t],d=3,D=1)	3933.17493248985	Range	389.7	Trim Var.	2351.74535475078
V(Y[t],d=0,D=2)	23022.65043915	Range	819	Trim Var.	13637.4877562041
V(Y[t],d=1,D=2)	2352.87163598807	Range	333.6	Trim Var.	1332.90434353283
V(Y[t],d=2,D=2)	3506.43060400436	Range	407	Trim Var.	2059.39114521349
V(Y[t],d=3,D=2)	10920.6579647792	Range	659.1	Trim Var.	6490.07402051023

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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Input Parameters & R Code