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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 05:10:16 -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/t1228738299vgausi25h8u050s.htm/, Retrieved Thu, 16 May 2024 19:43:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=30420, Retrieved Thu, 16 May 2024 19:43:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact189

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Variance Reduction Matrix] [VRM PAPER] [2008-12-08 12:10:16] [e11d930c9e2984715c66c796cf63ef19] [Current]
- RMPD    [Spectral Analysis] [SPECTRUM zonder a...] [2008-12-08 12:48:15] [547636b63517c1c2916a747d66b36ebf]
-   P       [Spectral Analysis] [SPECTRUM met aang...] [2008-12-08 12:53:34] [547636b63517c1c2916a747d66b36ebf]
- RMP         [Standard Deviation-Mean Plot] [SDMP PAPER LAMBDA...] [2008-12-08 13:40:16] [547636b63517c1c2916a747d66b36ebf]
- RM            [(Partial) Autocorrelation Function] [PACF zonder aagep...] [2008-12-08 13:59:46] [547636b63517c1c2916a747d66b36ebf]
-                 [(Partial) Autocorrelation Function] [PACF met aangepas...] [2008-12-08 14:08:36] [547636b63517c1c2916a747d66b36ebf]
-   P         [Spectral Analysis] [SPECTRUM met alle...] [2008-12-08 14:21:51] [547636b63517c1c2916a747d66b36ebf]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12300,00
12092,80
12380,80
12196,90
9455,00
13168,00
13427,90
11980,50
11884,80
11691,70
12233,80
14341,40
13130,70
12421,10
14285,80
12864,60
11160,20
14316,20
14388,70
14013,90
13419,00
12769,60
13315,50
15332,90
14243,00
13824,40
14962,90
13202,90
12199,00
15508,90
14199,80
15169,60
14058,00
13786,20
14147,90
16541,70
13587,50
15582,40
15802,80
14130,50
12923,20
15612,20
16033,70
16036,60
14037,80
15330,60
15038,30
17401,80
14992,50
16043,70
16929,60
15921,30
14417,20
15961,00
17851,90
16483,90
14215,50
17429,70
17839,50
17629,20

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'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=30420&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=30420&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30420&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'George Udny Yule' @ 72.249.76.132






Variance Reduction Matrix
V(Y[t],d=0,D=0)3266717.22620057Range8396.9Trim Var.2195746.37298393
V(Y[t],d=1,D=0)2609348.68158387Range6667.2Trim Var.1817456.76176343
V(Y[t],d=2,D=0)7245770.43095281Range11802.9Trim Var.4784037.57545626
V(Y[t],d=3,D=0)22394890.3811905Range20205.1Trim Var.15048042.4697490
V(Y[t],d=0,D=1)435273.896578014Range3456.7Trim Var.237644.863675958
V(Y[t],d=1,D=1)1074347.73583719Range4987.3Trim Var.622238.479902439
V(Y[t],d=2,D=1)3140958.90749759Range7609.4Trim Var.2021653.44766667
V(Y[t],d=3,D=1)9871961.7059091Range14127.9Trim Var.6168214.55762483
V(Y[t],d=0,D=2)805985.671587302Range3828.3Trim Var.484801.704153226
V(Y[t],d=1,D=2)1943355.06710924Range6469.4Trim Var.1095283.52584946
V(Y[t],d=2,D=2)6021749.63223708Range10707.2Trim Var.3277442.93627586
V(Y[t],d=3,D=2)19778922.2406440Range20017.9Trim Var.10845851.9343596

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 3266717.22620057 & Range & 8396.9 & Trim Var. & 2195746.37298393 \tabularnewline
V(Y[t],d=1,D=0) & 2609348.68158387 & Range & 6667.2 & Trim Var. & 1817456.76176343 \tabularnewline
V(Y[t],d=2,D=0) & 7245770.43095281 & Range & 11802.9 & Trim Var. & 4784037.57545626 \tabularnewline
V(Y[t],d=3,D=0) & 22394890.3811905 & Range & 20205.1 & Trim Var. & 15048042.4697490 \tabularnewline
V(Y[t],d=0,D=1) & 435273.896578014 & Range & 3456.7 & Trim Var. & 237644.863675958 \tabularnewline
V(Y[t],d=1,D=1) & 1074347.73583719 & Range & 4987.3 & Trim Var. & 622238.479902439 \tabularnewline
V(Y[t],d=2,D=1) & 3140958.90749759 & Range & 7609.4 & Trim Var. & 2021653.44766667 \tabularnewline
V(Y[t],d=3,D=1) & 9871961.7059091 & Range & 14127.9 & Trim Var. & 6168214.55762483 \tabularnewline
V(Y[t],d=0,D=2) & 805985.671587302 & Range & 3828.3 & Trim Var. & 484801.704153226 \tabularnewline
V(Y[t],d=1,D=2) & 1943355.06710924 & Range & 6469.4 & Trim Var. & 1095283.52584946 \tabularnewline
V(Y[t],d=2,D=2) & 6021749.63223708 & Range & 10707.2 & Trim Var. & 3277442.93627586 \tabularnewline
V(Y[t],d=3,D=2) & 19778922.2406440 & Range & 20017.9 & Trim Var. & 10845851.9343596 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30420&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]3266717.22620057[/C][C]Range[/C][C]8396.9[/C][C]Trim Var.[/C][C]2195746.37298393[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]2609348.68158387[/C][C]Range[/C][C]6667.2[/C][C]Trim Var.[/C][C]1817456.76176343[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]7245770.43095281[/C][C]Range[/C][C]11802.9[/C][C]Trim Var.[/C][C]4784037.57545626[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]22394890.3811905[/C][C]Range[/C][C]20205.1[/C][C]Trim Var.[/C][C]15048042.4697490[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]435273.896578014[/C][C]Range[/C][C]3456.7[/C][C]Trim Var.[/C][C]237644.863675958[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]1074347.73583719[/C][C]Range[/C][C]4987.3[/C][C]Trim Var.[/C][C]622238.479902439[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]3140958.90749759[/C][C]Range[/C][C]7609.4[/C][C]Trim Var.[/C][C]2021653.44766667[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]9871961.7059091[/C][C]Range[/C][C]14127.9[/C][C]Trim Var.[/C][C]6168214.55762483[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]805985.671587302[/C][C]Range[/C][C]3828.3[/C][C]Trim Var.[/C][C]484801.704153226[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]1943355.06710924[/C][C]Range[/C][C]6469.4[/C][C]Trim Var.[/C][C]1095283.52584946[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]6021749.63223708[/C][C]Range[/C][C]10707.2[/C][C]Trim Var.[/C][C]3277442.93627586[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]19778922.2406440[/C][C]Range[/C][C]20017.9[/C][C]Trim Var.[/C][C]10845851.9343596[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30420&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30420&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)3266717.22620057Range8396.9Trim Var.2195746.37298393
V(Y[t],d=1,D=0)2609348.68158387Range6667.2Trim Var.1817456.76176343
V(Y[t],d=2,D=0)7245770.43095281Range11802.9Trim Var.4784037.57545626
V(Y[t],d=3,D=0)22394890.3811905Range20205.1Trim Var.15048042.4697490
V(Y[t],d=0,D=1)435273.896578014Range3456.7Trim Var.237644.863675958
V(Y[t],d=1,D=1)1074347.73583719Range4987.3Trim Var.622238.479902439
V(Y[t],d=2,D=1)3140958.90749759Range7609.4Trim Var.2021653.44766667
V(Y[t],d=3,D=1)9871961.7059091Range14127.9Trim Var.6168214.55762483
V(Y[t],d=0,D=2)805985.671587302Range3828.3Trim Var.484801.704153226
V(Y[t],d=1,D=2)1943355.06710924Range6469.4Trim Var.1095283.52584946
V(Y[t],d=2,D=2)6021749.63223708Range10707.2Trim Var.3277442.93627586
V(Y[t],d=3,D=2)19778922.2406440Range20017.9Trim Var.10845851.9343596


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')