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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 computationTue, 02 Dec 2008 13:13:03 -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/02/t12282488593nfws6kh6j485ra.htm/, Retrieved Sun, 19 May 2024 12:36:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28342, Retrieved Sun, 19 May 2024 12:36:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact146

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] [Non stat time se...] [2008-12-02 20:13:03] [c5d6d05aee6be5527ac4a30a8c3b8fe5] [Current]
Feedback Forum
2008-12-06 14:09:09 [Thomas Plasschaert] [reply] 
juiste bewerking gedaan en tot de juiste conclusie gekomen.
2008-12-08 16:56:43 [Jonas Janssens] [reply] 
Juiste werkwijze voor het vinden van d en D.
2008-12-08 19:49:30 [5faab2fc6fb120339944528a32d48a04] [reply] 
differentiatie die nodig is om de meeste volatiliteit te verklaren hoort bij lijn 3.
2008-12-09 22:59:44 [Gert-Jan Geudens] [reply] 
Correct. Probeer ook de getrimde variantie (zoals reeds besproken in de feedback op Q3) niet uit het oog te verliezen.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
105,4
107,1
110,7
117,1
118,7
126,5
127,5
134,6
131,8
135,9
142,7
141,7
153,4
145
137,7
148,3
152,2
169,4
168,6
161,1
174,1
179
190,6
190
181,6
174,8
180,5
196,8
193,8
197
216,3
221,4
217,9
229,7
227,4
204,2
196,6
198,8
207,5
190,7
201,6
210,5
223,5
223,8
231,2
244
234,7
250,2
265,7
287,6
283,3
295,4
312,3
333,8
347,7
383,2
407,1
413,6
362,7
321,9
239,4

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28342&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]0 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=28342&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28342&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 time0 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Variance Reduction Matrix
V(Y[t],d=0,D=0)5669.4813442623Range308.2Trim Var.3155.94592162554
V(Y[t],d=1,D=0)315.850395480226Range118Trim Var.86.9484870719777
V(Y[t],d=2,D=0)256.151320864991Range85.1Trim Var.142.065631349782
V(Y[t],d=3,D=0)637.801488203267Range119.3Trim Var.417.117390648568
V(Y[t],d=0,D=1)2021.38736394558Range202.2Trim Var.1030.10944629014
V(Y[t],d=1,D=1)520.492335992908Range136.7Trim Var.158.379140534263
V(Y[t],d=2,D=1)476.14474560592Range88.7Trim Var.285.846219512195
V(Y[t],d=3,D=1)1218.58676811594Range147.9Trim Var.727.910641025641
V(Y[t],d=0,D=2)4347.42693693694Range258Trim Var.3070.77280303030
V(Y[t],d=1,D=2)1266.18342857143Range183.1Trim Var.424.968870967742
V(Y[t],d=2,D=2)1308.51761344538Range147.9Trim Var.872.999612903226
V(Y[t],d=3,D=2)3534.50200534759Range252.6Trim Var.2259.90464367816

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 5669.4813442623 & Range & 308.2 & Trim Var. & 3155.94592162554 \tabularnewline
V(Y[t],d=1,D=0) & 315.850395480226 & Range & 118 & Trim Var. & 86.9484870719777 \tabularnewline
V(Y[t],d=2,D=0) & 256.151320864991 & Range & 85.1 & Trim Var. & 142.065631349782 \tabularnewline
V(Y[t],d=3,D=0) & 637.801488203267 & Range & 119.3 & Trim Var. & 417.117390648568 \tabularnewline
V(Y[t],d=0,D=1) & 2021.38736394558 & Range & 202.2 & Trim Var. & 1030.10944629014 \tabularnewline
V(Y[t],d=1,D=1) & 520.492335992908 & Range & 136.7 & Trim Var. & 158.379140534263 \tabularnewline
V(Y[t],d=2,D=1) & 476.14474560592 & Range & 88.7 & Trim Var. & 285.846219512195 \tabularnewline
V(Y[t],d=3,D=1) & 1218.58676811594 & Range & 147.9 & Trim Var. & 727.910641025641 \tabularnewline
V(Y[t],d=0,D=2) & 4347.42693693694 & Range & 258 & Trim Var. & 3070.77280303030 \tabularnewline
V(Y[t],d=1,D=2) & 1266.18342857143 & Range & 183.1 & Trim Var. & 424.968870967742 \tabularnewline
V(Y[t],d=2,D=2) & 1308.51761344538 & Range & 147.9 & Trim Var. & 872.999612903226 \tabularnewline
V(Y[t],d=3,D=2) & 3534.50200534759 & Range & 252.6 & Trim Var. & 2259.90464367816 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28342&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]5669.4813442623[/C][C]Range[/C][C]308.2[/C][C]Trim Var.[/C][C]3155.94592162554[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]315.850395480226[/C][C]Range[/C][C]118[/C][C]Trim Var.[/C][C]86.9484870719777[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]256.151320864991[/C][C]Range[/C][C]85.1[/C][C]Trim Var.[/C][C]142.065631349782[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]637.801488203267[/C][C]Range[/C][C]119.3[/C][C]Trim Var.[/C][C]417.117390648568[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]2021.38736394558[/C][C]Range[/C][C]202.2[/C][C]Trim Var.[/C][C]1030.10944629014[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]520.492335992908[/C][C]Range[/C][C]136.7[/C][C]Trim Var.[/C][C]158.379140534263[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]476.14474560592[/C][C]Range[/C][C]88.7[/C][C]Trim Var.[/C][C]285.846219512195[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]1218.58676811594[/C][C]Range[/C][C]147.9[/C][C]Trim Var.[/C][C]727.910641025641[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]4347.42693693694[/C][C]Range[/C][C]258[/C][C]Trim Var.[/C][C]3070.77280303030[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]1266.18342857143[/C][C]Range[/C][C]183.1[/C][C]Trim Var.[/C][C]424.968870967742[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]1308.51761344538[/C][C]Range[/C][C]147.9[/C][C]Trim Var.[/C][C]872.999612903226[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]3534.50200534759[/C][C]Range[/C][C]252.6[/C][C]Trim Var.[/C][C]2259.90464367816[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28342&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28342&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)5669.4813442623Range308.2Trim Var.3155.94592162554
V(Y[t],d=1,D=0)315.850395480226Range118Trim Var.86.9484870719777
V(Y[t],d=2,D=0)256.151320864991Range85.1Trim Var.142.065631349782
V(Y[t],d=3,D=0)637.801488203267Range119.3Trim Var.417.117390648568
V(Y[t],d=0,D=1)2021.38736394558Range202.2Trim Var.1030.10944629014
V(Y[t],d=1,D=1)520.492335992908Range136.7Trim Var.158.379140534263
V(Y[t],d=2,D=1)476.14474560592Range88.7Trim Var.285.846219512195
V(Y[t],d=3,D=1)1218.58676811594Range147.9Trim Var.727.910641025641
V(Y[t],d=0,D=2)4347.42693693694Range258Trim Var.3070.77280303030
V(Y[t],d=1,D=2)1266.18342857143Range183.1Trim Var.424.968870967742
V(Y[t],d=2,D=2)1308.51761344538Range147.9Trim Var.872.999612903226
V(Y[t],d=3,D=2)3534.50200534759Range252.6Trim Var.2259.90464367816


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')