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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 computationMon, 08 Dec 2008 13:31:01 -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/t12287682998ttujix98h4h2ow.htm/, Retrieved Thu, 16 May 2024 14:43:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=30971, Retrieved Thu, 16 May 2024 14:43:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsARMA proces WS5 Q2: VRM totaal
Estimated Impact187

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Law of Averages] [Random Walk Simul...] [2008-11-25 18:31:28] [b98453cac15ba1066b407e146608df68]
F RM D  [(Partial) Autocorrelation Function] [non stationary ti...] [2008-12-02 20:37:52] [47f64d63202c1921bd27f3073f07a153]
F    D    [(Partial) Autocorrelation Function] [non stationary ti...] [2008-12-02 20:40:11] [47f64d63202c1921bd27f3073f07a153]
-           [(Partial) Autocorrelation Function] [non stationary ti...] [2008-12-02 20:41:59] [47f64d63202c1921bd27f3073f07a153]
F RM          [Variance Reduction Matrix] [non stationary ti...] [2008-12-02 20:44:40] [47f64d63202c1921bd27f3073f07a153]
F   P             [Variance Reduction Matrix] [ARMA proces WS5 Q...] [2008-12-08 20:31:01] [74c7506a1ea162af3aa8be25bcd05d28] [Current]
F RMP               [(Partial) Autocorrelation Function] [arma processen WS...] [2008-12-09 15:55:54] [47f64d63202c1921bd27f3073f07a153]
F RMP                 [Spectral Analysis] [arma processen WS...] [2008-12-09 16:01:45] [47f64d63202c1921bd27f3073f07a153]
F   P                 [(Partial) Autocorrelation Function] [arma processen WS...] [2008-12-09 16:10:15] [47f64d63202c1921bd27f3073f07a153]
Feedback Forum
2008-12-11 11:13:40 [72e979bcc364082694890d2eccc1a66f] [reply] 
De varianties leiden inderdaad tot verschillende oplossingen voor D en d. Om hier volledig uitsluitsel over te kunnen geven moeten we kijken wat de autocorrelation function en de spectrale analyse hierover weergeven.
2008-12-15 19:21:52 [Bénédicte Soens] [reply] 
Aangezien er een verschil is tussen de kleinste variantie van de gewone variantie en de getrimde variantie, moeten we verder onderzoeken hoe we moeten differentieren. Dit kan via de ACF en Spectral Analyse.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
8.4
8.4
8.4
8.6
8.9
8.8
8.3
7.5
7.2
7.5
8.8
9.3
9.3
8.7
8.2
8.3
8.5
8.6
8.6
8.2
8.1
8
8.6
8.7
8.8
8.5
8.4
8.5
8.7
8.7
8.6
8.5
8.3
8.1
8.2
8.1
8.1
7.9
7.9
7.9
8
8
7.9
8
7.7
7.2
7.5
7.3
7
7
7
7.2
7.3
7.1
6.8
6.6
6.2
6.2
6.8
6.9
6.8

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30971&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30971&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30971&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Variance Reduction Matrix
V(Y[t],d=0,D=0)0.55675956284153Range3.1Trim Var.0.304753401360544
V(Y[t],d=1,D=0)0.101649717514124Range2.1Trim Var.0.0363197586726998
V(Y[t],d=2,D=0)0.12947983635301Range1.8Trim Var.0.072564705882353
V(Y[t],d=3,D=0)0.270163339382940Range2.8Trim Var.0.134328808446456
V(Y[t],d=0,D=1)0.308333333333333Range2.4Trim Var.0.179623477297896
V(Y[t],d=1,D=1)0.0775487588652483Range1.2Trim Var.0.0382307692307692
V(Y[t],d=2,D=1)0.0757909343200741Range1.2Trim Var.0.0438397435897437
V(Y[t],d=3,D=1)0.160425120772947Range1.5Trim Var.0.0981987179487183
V(Y[t],d=0,D=2)0.248693693693694Range2.3Trim Var.0.155587121212121
V(Y[t],d=1,D=2)0.129230158730159Range1.50000000000000Trim Var.0.0761290322580644
V(Y[t],d=2,D=2)0.151042016806723Range1.70000000000000Trim Var.0.0849462365591397
V(Y[t],d=3,D=2)0.411203208556149Range2.59999999999999Trim Var.0.235402298850575

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 0.55675956284153 & Range & 3.1 & Trim Var. & 0.304753401360544 \tabularnewline
V(Y[t],d=1,D=0) & 0.101649717514124 & Range & 2.1 & Trim Var. & 0.0363197586726998 \tabularnewline
V(Y[t],d=2,D=0) & 0.12947983635301 & Range & 1.8 & Trim Var. & 0.072564705882353 \tabularnewline
V(Y[t],d=3,D=0) & 0.270163339382940 & Range & 2.8 & Trim Var. & 0.134328808446456 \tabularnewline
V(Y[t],d=0,D=1) & 0.308333333333333 & Range & 2.4 & Trim Var. & 0.179623477297896 \tabularnewline
V(Y[t],d=1,D=1) & 0.0775487588652483 & Range & 1.2 & Trim Var. & 0.0382307692307692 \tabularnewline
V(Y[t],d=2,D=1) & 0.0757909343200741 & Range & 1.2 & Trim Var. & 0.0438397435897437 \tabularnewline
V(Y[t],d=3,D=1) & 0.160425120772947 & Range & 1.5 & Trim Var. & 0.0981987179487183 \tabularnewline
V(Y[t],d=0,D=2) & 0.248693693693694 & Range & 2.3 & Trim Var. & 0.155587121212121 \tabularnewline
V(Y[t],d=1,D=2) & 0.129230158730159 & Range & 1.50000000000000 & Trim Var. & 0.0761290322580644 \tabularnewline
V(Y[t],d=2,D=2) & 0.151042016806723 & Range & 1.70000000000000 & Trim Var. & 0.0849462365591397 \tabularnewline
V(Y[t],d=3,D=2) & 0.411203208556149 & Range & 2.59999999999999 & Trim Var. & 0.235402298850575 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30971&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]0.55675956284153[/C][C]Range[/C][C]3.1[/C][C]Trim Var.[/C][C]0.304753401360544[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]0.101649717514124[/C][C]Range[/C][C]2.1[/C][C]Trim Var.[/C][C]0.0363197586726998[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]0.12947983635301[/C][C]Range[/C][C]1.8[/C][C]Trim Var.[/C][C]0.072564705882353[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]0.270163339382940[/C][C]Range[/C][C]2.8[/C][C]Trim Var.[/C][C]0.134328808446456[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]0.308333333333333[/C][C]Range[/C][C]2.4[/C][C]Trim Var.[/C][C]0.179623477297896[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.0775487588652483[/C][C]Range[/C][C]1.2[/C][C]Trim Var.[/C][C]0.0382307692307692[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]0.0757909343200741[/C][C]Range[/C][C]1.2[/C][C]Trim Var.[/C][C]0.0438397435897437[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]0.160425120772947[/C][C]Range[/C][C]1.5[/C][C]Trim Var.[/C][C]0.0981987179487183[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]0.248693693693694[/C][C]Range[/C][C]2.3[/C][C]Trim Var.[/C][C]0.155587121212121[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]0.129230158730159[/C][C]Range[/C][C]1.50000000000000[/C][C]Trim Var.[/C][C]0.0761290322580644[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]0.151042016806723[/C][C]Range[/C][C]1.70000000000000[/C][C]Trim Var.[/C][C]0.0849462365591397[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]0.411203208556149[/C][C]Range[/C][C]2.59999999999999[/C][C]Trim Var.[/C][C]0.235402298850575[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30971&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30971&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)0.55675956284153Range3.1Trim Var.0.304753401360544
V(Y[t],d=1,D=0)0.101649717514124Range2.1Trim Var.0.0363197586726998
V(Y[t],d=2,D=0)0.12947983635301Range1.8Trim Var.0.072564705882353
V(Y[t],d=3,D=0)0.270163339382940Range2.8Trim Var.0.134328808446456
V(Y[t],d=0,D=1)0.308333333333333Range2.4Trim Var.0.179623477297896
V(Y[t],d=1,D=1)0.0775487588652483Range1.2Trim Var.0.0382307692307692
V(Y[t],d=2,D=1)0.0757909343200741Range1.2Trim Var.0.0438397435897437
V(Y[t],d=3,D=1)0.160425120772947Range1.5Trim Var.0.0981987179487183
V(Y[t],d=0,D=2)0.248693693693694Range2.3Trim Var.0.155587121212121
V(Y[t],d=1,D=2)0.129230158730159Range1.50000000000000Trim Var.0.0761290322580644
V(Y[t],d=2,D=2)0.151042016806723Range1.70000000000000Trim Var.0.0849462365591397
V(Y[t],d=3,D=2)0.411203208556149Range2.59999999999999Trim Var.0.235402298850575


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 1 ; par3 = 1 ; par4 = 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')