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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, 06 Dec 2011 15:14:08 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/06/t1323202479qco4ma4240n6om3.htm/, Retrieved Mon, 29 Apr 2024 00:36:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=151880, Retrieved Mon, 29 Apr 2024 00:36:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact241

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] [] [2008-12-14 11:54:22] [d2d412c7f4d35ffbf5ee5ee89db327d4]
- RMP     [Variance Reduction Matrix] [] [2011-12-06 20:14:08] [d76b387543b13b5e3afd8ff9e5fdc89f] [Current]
- RM        [Variance Reduction Matrix] [Paper deel 2f] [2011-12-19 22:34:31] [3346191a817a30d0b56421a47a7031a4]
- R P       [Variance Reduction Matrix] [VRM] [2012-11-26 21:49:19] [dbdfdab7c884aa7a69290945f2923e51]
- R         [Variance Reduction Matrix] [VRM] [2012-12-07 19:25:59] [ec67509cb0a58a77552cc42e4bdf733e]
- R         [Variance Reduction Matrix] [Paper] [2012-12-12 14:26:09] [9d44b52ac7f20a3e9be7c3c8470fe2cd]
- R           [Variance Reduction Matrix] [paper] [2012-12-18 19:39:26] [fa543719fe3f8358943b948de15add90]
- RM        [Variance Reduction Matrix] [Paper Deel 4 Arima 2] [2012-12-21 14:37:36] [2972d443360a042d7188069add54b356]
- RM        [Variance Reduction Matrix] [WS 9] [2013-12-04 09:36:11] [a33425df4f50c4c8e40ef78287b40411]
- RM        [Variance Reduction Matrix] [blog 1] [2014-11-26 11:47:43] [388e7fc45813588c973a58470d39020f]
- RM        [Variance Reduction Matrix] [asdfasdfasdfasdf] [2014-11-26 11:51:07] [a21a52637ee232286cdd7eb4387e60d4]
- RMP         [Spectral Analysis] [2323] [2014-11-26 11:57:21] [a21a52637ee232286cdd7eb4387e60d4]
- RMP       [Spectral Analysis] [blog 3] [2014-11-26 12:06:16] [388e7fc45813588c973a58470d39020f]
- RMP       [Variance Reduction Matrix] [Ws 9 VRM 2] [2014-11-26 14:18:13] [27d418b925e6b9b020a05307ec6c6034]
- RMP       [Spectral Analysis] [WS 9 SA 3] [2014-11-26 14:19:22] [27d418b925e6b9b020a05307ec6c6034]
- RMP       [Variance Reduction Matrix] [] [2014-11-26 19:06:57] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RM        [Variance Reduction Matrix] [w9 vrm] [2014-11-27 09:36:08] [673773038936aef3a5778d7e6bda5c1e]
- RM        [Variance Reduction Matrix] [ws 9 m] [2014-11-27 22:18:20] [be945163e51ed825733188af308451be]
- RM        [Standard Deviation-Mean Plot] [] [2015-01-14 15:50:16] [a973c0e834bbe3ac475ff4c54470c2b0]
- RM        [Variance Reduction Matrix] [] [2015-01-14 15:54:59] [a973c0e834bbe3ac475ff4c54470c2b0]
- RMP       [(Partial) Autocorrelation Function] [] [2015-01-14 15:58:45] [a973c0e834bbe3ac475ff4c54470c2b0]
- RMP       [Spectral Analysis] [] [2015-01-14 16:03:49] [a973c0e834bbe3ac475ff4c54470c2b0]
- RMP       [ARIMA Backward Selection] [] [2015-01-14 16:09:14] [a973c0e834bbe3ac475ff4c54470c2b0]
- RMP       [(Partial) Autocorrelation Function] [] [2015-01-14 16:19:53] [a973c0e834bbe3ac475ff4c54470c2b0]
- RMP       [ARIMA Backward Selection] [] [2015-01-14 16:20:55] [a973c0e834bbe3ac475ff4c54470c2b0]
- RM          [ARIMA Backward Selection] [] [2015-01-14 16:35:28] [a973c0e834bbe3ac475ff4c54470c2b0]
- RMP       [ARIMA Forecasting] [] [2015-01-14 16:22:20] [a973c0e834bbe3ac475ff4c54470c2b0]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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

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'Gertrude Mary Cox' @ cox.wessa.net

\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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=151880&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=151880&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=151880&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'Gertrude Mary Cox' @ cox.wessa.net






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.2009.9231372549
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. & 2009.9231372549 \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=151880&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]2009.9231372549[/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=151880&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=151880&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)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.2009.9231372549
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


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(myx,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')
bitmap(file='pic0.png')
op <- par(mfrow=c(2,2))
plot(x,type='l',xlab='time',ylab='value',main='d=0, D=0')
plot(diff(x,lag=1,differences=1),type='l',xlab='time',ylab='value',main='d=1, D=0')
plot(diff(x,lag=par1,differences=1),type='l',xlab='time',ylab='value',main='d=0, D=1')
plot(diff(diff(x,lag=1,differences=1),lag=par1,differences=1),type='l',xlab='time',ylab='value',main='d=1, D=1')
par(op)
dev.off()