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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, 17 Dec 2008 09:00:59 -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/17/t1229529699ka54bs5cex2jbnd.htm/, Retrieved Fri, 17 May 2024 18:43:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=34429, Retrieved Fri, 17 May 2024 18:43:03 +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)
F     [Univariate Data Series] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
F RMPD  [Cross Correlation Function] [Q7 - zonder trans...] [2008-12-01 20:04:13] [299afd6311e4c20059ea2f05c8dd029d]
F RM D    [Variance Reduction Matrix] [Q8] [2008-12-01 20:20:44] [299afd6311e4c20059ea2f05c8dd029d]
F    D      [Variance Reduction Matrix] [Q8 - 2] [2008-12-01 20:25:07] [299afd6311e4c20059ea2f05c8dd029d]
F RM D        [Standard Deviation-Mean Plot] [Deel 2: Step 1] [2008-12-08 20:09:35] [299afd6311e4c20059ea2f05c8dd029d]
- RM D          [Variance Reduction Matrix] [Deel 2: Step 2 - VRM] [2008-12-08 20:13:17] [299afd6311e4c20059ea2f05c8dd029d]
-                   [Variance Reduction Matrix] [Totale Uitvoer - VRM] [2008-12-17 16:00:59] [5e2b1e7aa808f9f0d23fd35605d4968f] [Current]
-  MPD                [Variance Reduction Matrix] [] [2010-12-24 11:50:15] [4dfa50539945b119a90a7606969443b9]
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Dataseries X:
14291.1
14205.3
15859.4
15258.9
15498.6
15106.5
15023.6
12083
15761.3
16943
15070.3
13659.6
14768.9
14725.1
15998.1
15370.6
14956.9
15469.7
15101.8
11703.7
16283.6
16726.5
14968.9
14861
14583.3
15305.8
17903.9
16379.4
15420.3
17870.5
15912.8
13866.5
17823.2
17872
17420.4
16704.4
15991.2
16583.6
19123.5
17838.7
17209.4
18586.5
16258.1
15141.6
19202.1
17746.5
19090.1
18040.3
17515.5
17751.8
21072.4
17170
19439.5
19795.4
17574.9
16165.4
19464.6
19932.1
19961.2
17343.4
18924.2
18574.1
21350.6
18594.6
19823.1
20844.4
19640.2
17735.4
19813.6
22160
20664.3
17877.4




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 & 0 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34429&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34429&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34429&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 time0 seconds
R Server'George Udny Yule' @ 72.249.76.132







Variance Reduction Matrix
V(Y[t],d=0,D=0)4832793.15577465Range10456.3Trim Var.3064260.11633929
V(Y[t],d=1,D=0)3634241.4792998Range8482.3Trim Var.2334483.38166411
V(Y[t],d=2,D=0)9691955.65157143Range15201Trim Var.5801326.25553675
V(Y[t],d=3,D=0)29625064.9309122Range25509.9Trim Var.17798047.641388
V(Y[t],d=0,D=1)656381.730878531Range3148.4Trim Var.474735.92327044
V(Y[t],d=1,D=1)1227343.92943308Range5516.4Trim Var.821821.471770682
V(Y[t],d=2,D=1)3950963.89436479Range9436.4Trim Var.2567329.95337858
V(Y[t],d=3,D=1)13367969.5156642Range18351.1Trim Var.8594526.78198431
V(Y[t],d=0,D=2)1422191.23297429Range4680.9Trim Var.897005.415522649
V(Y[t],d=1,D=2)2578058.82563367Range7703.8Trim Var.1294477.20869512
V(Y[t],d=2,D=2)8164417.3338744Range13330.2Trim Var.4180836.74151282
V(Y[t],d=3,D=2)27821974.7310909Range26122.8Trim Var.14431839.1346289

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 4832793.15577465 & Range & 10456.3 & Trim Var. & 3064260.11633929 \tabularnewline
V(Y[t],d=1,D=0) & 3634241.4792998 & Range & 8482.3 & Trim Var. & 2334483.38166411 \tabularnewline
V(Y[t],d=2,D=0) & 9691955.65157143 & Range & 15201 & Trim Var. & 5801326.25553675 \tabularnewline
V(Y[t],d=3,D=0) & 29625064.9309122 & Range & 25509.9 & Trim Var. & 17798047.641388 \tabularnewline
V(Y[t],d=0,D=1) & 656381.730878531 & Range & 3148.4 & Trim Var. & 474735.92327044 \tabularnewline
V(Y[t],d=1,D=1) & 1227343.92943308 & Range & 5516.4 & Trim Var. & 821821.471770682 \tabularnewline
V(Y[t],d=2,D=1) & 3950963.89436479 & Range & 9436.4 & Trim Var. & 2567329.95337858 \tabularnewline
V(Y[t],d=3,D=1) & 13367969.5156642 & Range & 18351.1 & Trim Var. & 8594526.78198431 \tabularnewline
V(Y[t],d=0,D=2) & 1422191.23297429 & Range & 4680.9 & Trim Var. & 897005.415522649 \tabularnewline
V(Y[t],d=1,D=2) & 2578058.82563367 & Range & 7703.8 & Trim Var. & 1294477.20869512 \tabularnewline
V(Y[t],d=2,D=2) & 8164417.3338744 & Range & 13330.2 & Trim Var. & 4180836.74151282 \tabularnewline
V(Y[t],d=3,D=2) & 27821974.7310909 & Range & 26122.8 & Trim Var. & 14431839.1346289 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34429&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]4832793.15577465[/C][C]Range[/C][C]10456.3[/C][C]Trim Var.[/C][C]3064260.11633929[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]3634241.4792998[/C][C]Range[/C][C]8482.3[/C][C]Trim Var.[/C][C]2334483.38166411[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]9691955.65157143[/C][C]Range[/C][C]15201[/C][C]Trim Var.[/C][C]5801326.25553675[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]29625064.9309122[/C][C]Range[/C][C]25509.9[/C][C]Trim Var.[/C][C]17798047.641388[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]656381.730878531[/C][C]Range[/C][C]3148.4[/C][C]Trim Var.[/C][C]474735.92327044[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]1227343.92943308[/C][C]Range[/C][C]5516.4[/C][C]Trim Var.[/C][C]821821.471770682[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]3950963.89436479[/C][C]Range[/C][C]9436.4[/C][C]Trim Var.[/C][C]2567329.95337858[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]13367969.5156642[/C][C]Range[/C][C]18351.1[/C][C]Trim Var.[/C][C]8594526.78198431[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]1422191.23297429[/C][C]Range[/C][C]4680.9[/C][C]Trim Var.[/C][C]897005.415522649[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]2578058.82563367[/C][C]Range[/C][C]7703.8[/C][C]Trim Var.[/C][C]1294477.20869512[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]8164417.3338744[/C][C]Range[/C][C]13330.2[/C][C]Trim Var.[/C][C]4180836.74151282[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]27821974.7310909[/C][C]Range[/C][C]26122.8[/C][C]Trim Var.[/C][C]14431839.1346289[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34429&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34429&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)4832793.15577465Range10456.3Trim Var.3064260.11633929
V(Y[t],d=1,D=0)3634241.4792998Range8482.3Trim Var.2334483.38166411
V(Y[t],d=2,D=0)9691955.65157143Range15201Trim Var.5801326.25553675
V(Y[t],d=3,D=0)29625064.9309122Range25509.9Trim Var.17798047.641388
V(Y[t],d=0,D=1)656381.730878531Range3148.4Trim Var.474735.92327044
V(Y[t],d=1,D=1)1227343.92943308Range5516.4Trim Var.821821.471770682
V(Y[t],d=2,D=1)3950963.89436479Range9436.4Trim Var.2567329.95337858
V(Y[t],d=3,D=1)13367969.5156642Range18351.1Trim Var.8594526.78198431
V(Y[t],d=0,D=2)1422191.23297429Range4680.9Trim Var.897005.415522649
V(Y[t],d=1,D=2)2578058.82563367Range7703.8Trim Var.1294477.20869512
V(Y[t],d=2,D=2)8164417.3338744Range13330.2Trim Var.4180836.74151282
V(Y[t],d=3,D=2)27821974.7310909Range26122.8Trim Var.14431839.1346289



Parameters (Session):
par1 = 12 ;
Parameters (R input):
par1 = 12 ; par2 = ; par3 = ; par4 = ; par5 = ; par6 = ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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')