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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 computationSat, 06 Dec 2008 07:40:33 -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/06/t1228574606n61p0a3bkc6c9bo.htm/, Retrieved Fri, 17 May 2024 01:41:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=29660, Retrieved Fri, 17 May 2024 01:41:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact199

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] [Identification an...] [2008-12-04 19:36:54] [063e4b67ad7d3a8a83eccec794cd5aa7]
F    D    [Variance Reduction Matrix] [Eigen tijdreeks V...] [2008-12-06 14:21:42] [063e4b67ad7d3a8a83eccec794cd5aa7]
F    D        [Variance Reduction Matrix] [Eigen tijdreeks V...] [2008-12-06 14:40:33] [6797a1f4a60918966297e9d9220cabc2] [Current]
Feedback Forum
2008-12-15 18:40:31 [Jeroen Michel] [reply] 
Hier maakt de student gebruik van een correcte module. De output is correct en hier valt weinig aan toe te voegen.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
6.2
6.1
5.9
5.6
5.5
5.5
5.6
5.7
5.6
5.4
5.3
5.3
5.4
5.5
5.6
5.7
5.8
5.8
5.7
5.9
6.1
6.4
6.4
6.3
6.2
6.2
6.3
6.5
6.6
6.6
6.7
6.6
6.7
7
7.2
7.3
7.5
7.6
7.7
7.8
7.8
7.7
7.6
7.6
7.7
7.8
7.8
7.8
7.7
7.6
7.4
7.1
7.1
7.3
7.6
7.8
7.7
7.6
7.5
7.5
7.5
7.6
7.6
7.7
7.8
7.7
7.6
7.6
7.6
7.7
7.8
7.8
7.9
7.9
7.8
7.8
7.7
7.5
7.1
6.9
7.1
7.1
7.1
7
6.9
6.8
6.7
6.8
6.8
6.7
6.8
6.7
6.6
6.4
6.4
6.4
6.5
6.5
6.4
6.3
6.2
6.3

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=29660&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=29660&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29660&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)0.622446126965638Range2.6Trim Var.0.447330623306233
V(Y[t],d=1,D=0)0.0172990099009901Range0.700000000000001Trim Var.0.00779900088157508
V(Y[t],d=2,D=0)0.0165616161616162Range0.699999999999999Trim Var.0.0099948927477017
V(Y[t],d=3,D=0)0.0341743970315399Range1Trim Var.0.0199795709908069
V(Y[t],d=0,D=1)0.443965043695381Range2.5Trim Var.0.325935126582278
V(Y[t],d=1,D=1)0.0408886618998979Range0.9Trim Var.0.0233543859649123
V(Y[t],d=2,D=1)0.0383908045977012Range0.900000000000001Trim Var.0.0205052631578948
V(Y[t],d=3,D=1)0.0730179096498264Range1.50000000000000Trim Var.0.03473000683527
V(Y[t],d=0,D=2)0.6601998001998Range3.6Trim Var.0.440722567287785
V(Y[t],d=1,D=2)0.111332877648667Range1.60000000000000Trim Var.0.0728175618073316
V(Y[t],d=2,D=2)0.104771929824562Range1.60000000000000Trim Var.0.0558625987708517
V(Y[t],d=3,D=2)0.206605405405406Range2.4Trim Var.0.100574400723654

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 0.622446126965638 & Range & 2.6 & Trim Var. & 0.447330623306233 \tabularnewline
V(Y[t],d=1,D=0) & 0.0172990099009901 & Range & 0.700000000000001 & Trim Var. & 0.00779900088157508 \tabularnewline
V(Y[t],d=2,D=0) & 0.0165616161616162 & Range & 0.699999999999999 & Trim Var. & 0.0099948927477017 \tabularnewline
V(Y[t],d=3,D=0) & 0.0341743970315399 & Range & 1 & Trim Var. & 0.0199795709908069 \tabularnewline
V(Y[t],d=0,D=1) & 0.443965043695381 & Range & 2.5 & Trim Var. & 0.325935126582278 \tabularnewline
V(Y[t],d=1,D=1) & 0.0408886618998979 & Range & 0.9 & Trim Var. & 0.0233543859649123 \tabularnewline
V(Y[t],d=2,D=1) & 0.0383908045977012 & Range & 0.900000000000001 & Trim Var. & 0.0205052631578948 \tabularnewline
V(Y[t],d=3,D=1) & 0.0730179096498264 & Range & 1.50000000000000 & Trim Var. & 0.03473000683527 \tabularnewline
V(Y[t],d=0,D=2) & 0.6601998001998 & Range & 3.6 & Trim Var. & 0.440722567287785 \tabularnewline
V(Y[t],d=1,D=2) & 0.111332877648667 & Range & 1.60000000000000 & Trim Var. & 0.0728175618073316 \tabularnewline
V(Y[t],d=2,D=2) & 0.104771929824562 & Range & 1.60000000000000 & Trim Var. & 0.0558625987708517 \tabularnewline
V(Y[t],d=3,D=2) & 0.206605405405406 & Range & 2.4 & Trim Var. & 0.100574400723654 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29660&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]0.622446126965638[/C][C]Range[/C][C]2.6[/C][C]Trim Var.[/C][C]0.447330623306233[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]0.0172990099009901[/C][C]Range[/C][C]0.700000000000001[/C][C]Trim Var.[/C][C]0.00779900088157508[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]0.0165616161616162[/C][C]Range[/C][C]0.699999999999999[/C][C]Trim Var.[/C][C]0.0099948927477017[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]0.0341743970315399[/C][C]Range[/C][C]1[/C][C]Trim Var.[/C][C]0.0199795709908069[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]0.443965043695381[/C][C]Range[/C][C]2.5[/C][C]Trim Var.[/C][C]0.325935126582278[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.0408886618998979[/C][C]Range[/C][C]0.9[/C][C]Trim Var.[/C][C]0.0233543859649123[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]0.0383908045977012[/C][C]Range[/C][C]0.900000000000001[/C][C]Trim Var.[/C][C]0.0205052631578948[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]0.0730179096498264[/C][C]Range[/C][C]1.50000000000000[/C][C]Trim Var.[/C][C]0.03473000683527[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]0.6601998001998[/C][C]Range[/C][C]3.6[/C][C]Trim Var.[/C][C]0.440722567287785[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]0.111332877648667[/C][C]Range[/C][C]1.60000000000000[/C][C]Trim Var.[/C][C]0.0728175618073316[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]0.104771929824562[/C][C]Range[/C][C]1.60000000000000[/C][C]Trim Var.[/C][C]0.0558625987708517[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]0.206605405405406[/C][C]Range[/C][C]2.4[/C][C]Trim Var.[/C][C]0.100574400723654[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29660&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29660&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)0.622446126965638Range2.6Trim Var.0.447330623306233
V(Y[t],d=1,D=0)0.0172990099009901Range0.700000000000001Trim Var.0.00779900088157508
V(Y[t],d=2,D=0)0.0165616161616162Range0.699999999999999Trim Var.0.0099948927477017
V(Y[t],d=3,D=0)0.0341743970315399Range1Trim Var.0.0199795709908069
V(Y[t],d=0,D=1)0.443965043695381Range2.5Trim Var.0.325935126582278
V(Y[t],d=1,D=1)0.0408886618998979Range0.9Trim Var.0.0233543859649123
V(Y[t],d=2,D=1)0.0383908045977012Range0.900000000000001Trim Var.0.0205052631578948
V(Y[t],d=3,D=1)0.0730179096498264Range1.50000000000000Trim Var.0.03473000683527
V(Y[t],d=0,D=2)0.6601998001998Range3.6Trim Var.0.440722567287785
V(Y[t],d=1,D=2)0.111332877648667Range1.60000000000000Trim Var.0.0728175618073316
V(Y[t],d=2,D=2)0.104771929824562Range1.60000000000000Trim Var.0.0558625987708517
V(Y[t],d=3,D=2)0.206605405405406Range2.4Trim Var.0.100574400723654


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')