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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 07:05:06 -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/t1228745134husd1qplja9nqq1.htm/, Retrieved Thu, 16 May 2024 10:22:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=30500, Retrieved Thu, 16 May 2024 10:22:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsVRM
Estimated Impact175

Tree of Dependent Computations

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] [ARMA processing Q2] [2008-12-08 12:43:16] [c96f3dce3a823a83b6ede18389e1cfd4]
F    D      [Variance Reduction Matrix] [ARMA processing Q...] [2008-12-08 14:05:06] [3bdbbe597ac6c61989658933956ee6ac] [Current]
Feedback Forum
2008-12-14 11:28:50 [Gert-Jan Geudens] [reply] 
Goede conclusie. Vergeet ook hier zeker niet -in het geval van outliers- naar de laatste kolom met de getrimde variantie te kijken. Bij de feedback op je gevonden VRM bij step 2 hebben reeds uitgelegd waarom. Je link van deze VRM kan hier terugvinden :
http://www.freestatistics.org/blog/index.php?v=date/2008/Dec/08/t12287402623cdhf7jtiaucdc1.htm

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 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=30500&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=30500&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30500&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)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=30500&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=30500&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30500&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 = 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')