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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 computationWed, 15 Dec 2010 16:39:48 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/15/t1292431117y09buappoxwejrm.htm/, Retrieved Tue, 30 Apr 2024 23:50:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=110550, Retrieved Tue, 30 Apr 2024 23:50:25 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact216
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Variance Reduction Matrix] [Unemployment] [2010-11-29 09:29:57] [b98453cac15ba1066b407e146608df68]
-   PD    [Variance Reduction Matrix] [] [2010-12-15 16:39:48] [64cdeb58b12a5b72c79150d12c763b6f] [Current]
-    D      [Variance Reduction Matrix] [] [2010-12-17 08:24:47] [4dfa50539945b119a90a7606969443b9]
- R           [Variance Reduction Matrix] [] [2010-12-17 11:46:46] [c6813a60da787bb62b5d86150b8926dd]
- RM D          [Standard Deviation-Mean Plot] [] [2010-12-17 12:01:15] [c6813a60da787bb62b5d86150b8926dd]
-    D            [Standard Deviation-Mean Plot] [] [2010-12-27 21:00:10] [c6813a60da787bb62b5d86150b8926dd]
- R  D              [Standard Deviation-Mean Plot] [standard deviatio...] [2011-12-21 13:50:59] [74be16979710d4c4e7c6647856088456]
-  M                  [Standard Deviation-Mean Plot] [autocorrelatie] [2011-12-22 09:57:14] [f1aa04283d83c25edc8ae3bb0d0fb93e]
- R P               [Standard Deviation-Mean Plot] [Deel 4: ARIMA Sta...] [2012-12-13 14:56:50] [b4e5b8b5af0253f45dc68b47bb41cf13]
-    D          [Variance Reduction Matrix] [] [2010-12-27 20:49:16] [c6813a60da787bb62b5d86150b8926dd]
- R P             [Variance Reduction Matrix] [Deel 4: ARIMA: va...] [2012-12-13 14:43:53] [b4e5b8b5af0253f45dc68b47bb41cf13]
- R           [Variance Reduction Matrix] [stat in the mean ...] [2012-12-02 18:50:27] [74be16979710d4c4e7c6647856088456]
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Dataseries X:
46
62
66
59
58
61
41
27
58
70
49
59
44
36
72
45
56
54
53
35
61
52
47
51
52
63
74
45
51
64
36
30
55
64
39
40
63
45
59
55
40
64
27
28
45
57
45
69
60
56
58
50
51
53
37
22
55
70
62
58
39
49
58
47
42
62
39
40
72
70
54
65




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=110550&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=110550&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110550&T=0

As an alternative you can also use a 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)145.730633802817Range52Trim Var.87.8913273400317
V(Y[t],d=1,D=0)271.827364185111Range73Trim Var.176.435227854583
V(Y[t],d=2,D=0)726.849896480331Range111Trim Var.483.098907103825
V(Y[t],d=3,D=0)2183.95524296675Range208Trim Var.1418.15519125683
V(Y[t],d=0,D=1)131.779378531073Range55Trim Var.79.232946298984
V(Y[t],d=1,D=1)263.924605493863Range64Trim Var.201.459361393324
V(Y[t],d=2,D=1)797.136418632789Range111Trim Var.587.843137254902
V(Y[t],d=3,D=1)2651.60526315789Range209Trim Var.2009.92313725490
V(Y[t],d=0,D=2)391.871897163121Range98Trim Var.211.112659698026
V(Y[t],d=1,D=2)831.144310823312Range100Trim Var.597
V(Y[t],d=2,D=2)2526.44444444444Range197Trim Var.1816.76346153846
V(Y[t],d=3,D=2)8301.16161616162Range332Trim Var.5960.75438596491

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 145.730633802817 & Range & 52 & Trim Var. & 87.8913273400317 \tabularnewline
V(Y[t],d=1,D=0) & 271.827364185111 & Range & 73 & Trim Var. & 176.435227854583 \tabularnewline
V(Y[t],d=2,D=0) & 726.849896480331 & Range & 111 & Trim Var. & 483.098907103825 \tabularnewline
V(Y[t],d=3,D=0) & 2183.95524296675 & Range & 208 & Trim Var. & 1418.15519125683 \tabularnewline
V(Y[t],d=0,D=1) & 131.779378531073 & Range & 55 & Trim Var. & 79.232946298984 \tabularnewline
V(Y[t],d=1,D=1) & 263.924605493863 & Range & 64 & Trim Var. & 201.459361393324 \tabularnewline
V(Y[t],d=2,D=1) & 797.136418632789 & Range & 111 & Trim Var. & 587.843137254902 \tabularnewline
V(Y[t],d=3,D=1) & 2651.60526315789 & Range & 209 & Trim Var. & 2009.92313725490 \tabularnewline
V(Y[t],d=0,D=2) & 391.871897163121 & Range & 98 & Trim Var. & 211.112659698026 \tabularnewline
V(Y[t],d=1,D=2) & 831.144310823312 & Range & 100 & Trim Var. & 597 \tabularnewline
V(Y[t],d=2,D=2) & 2526.44444444444 & Range & 197 & Trim Var. & 1816.76346153846 \tabularnewline
V(Y[t],d=3,D=2) & 8301.16161616162 & Range & 332 & Trim Var. & 5960.75438596491 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110550&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]145.730633802817[/C][C]Range[/C][C]52[/C][C]Trim Var.[/C][C]87.8913273400317[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]271.827364185111[/C][C]Range[/C][C]73[/C][C]Trim Var.[/C][C]176.435227854583[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]726.849896480331[/C][C]Range[/C][C]111[/C][C]Trim Var.[/C][C]483.098907103825[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]2183.95524296675[/C][C]Range[/C][C]208[/C][C]Trim Var.[/C][C]1418.15519125683[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]131.779378531073[/C][C]Range[/C][C]55[/C][C]Trim Var.[/C][C]79.232946298984[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]263.924605493863[/C][C]Range[/C][C]64[/C][C]Trim Var.[/C][C]201.459361393324[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]797.136418632789[/C][C]Range[/C][C]111[/C][C]Trim Var.[/C][C]587.843137254902[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]2651.60526315789[/C][C]Range[/C][C]209[/C][C]Trim Var.[/C][C]2009.92313725490[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]391.871897163121[/C][C]Range[/C][C]98[/C][C]Trim Var.[/C][C]211.112659698026[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]831.144310823312[/C][C]Range[/C][C]100[/C][C]Trim Var.[/C][C]597[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]2526.44444444444[/C][C]Range[/C][C]197[/C][C]Trim Var.[/C][C]1816.76346153846[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]8301.16161616162[/C][C]Range[/C][C]332[/C][C]Trim Var.[/C][C]5960.75438596491[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110550&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110550&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Variance Reduction Matrix
V(Y[t],d=0,D=0)145.730633802817Range52Trim Var.87.8913273400317
V(Y[t],d=1,D=0)271.827364185111Range73Trim Var.176.435227854583
V(Y[t],d=2,D=0)726.849896480331Range111Trim Var.483.098907103825
V(Y[t],d=3,D=0)2183.95524296675Range208Trim Var.1418.15519125683
V(Y[t],d=0,D=1)131.779378531073Range55Trim Var.79.232946298984
V(Y[t],d=1,D=1)263.924605493863Range64Trim Var.201.459361393324
V(Y[t],d=2,D=1)797.136418632789Range111Trim Var.587.843137254902
V(Y[t],d=3,D=1)2651.60526315789Range209Trim Var.2009.92313725490
V(Y[t],d=0,D=2)391.871897163121Range98Trim Var.211.112659698026
V(Y[t],d=1,D=2)831.144310823312Range100Trim Var.597
V(Y[t],d=2,D=2)2526.44444444444Range197Trim Var.1816.76346153846
V(Y[t],d=3,D=2)8301.16161616162Range332Trim Var.5960.75438596491



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')