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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 computationThu, 16 Dec 2010 18:53:37 +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/16/t1292525490d11pjx9b6hwkcek.htm/, Retrieved Tue, 30 Apr 2024 03:46:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=111185, Retrieved Tue, 30 Apr 2024 03:46:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact164

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Q1 The Seatbeltlaw] [2007-11-14 19:27:43] [8cd6641b921d30ebe00b648d1481bba0]
- RMPD  [Multiple Regression] [Seatbelt] [2009-11-12 13:54:52] [b98453cac15ba1066b407e146608df68]
-    D    [Multiple Regression] [WS7] [2009-11-18 17:01:04] [8b1aef4e7013bd33fbc2a5833375c5f5]
-   PD      [Multiple Regression] [WS7(2)] [2009-11-20 19:01:46] [7d268329e554b8694908ba13e6e6f258]
-   P         [Multiple Regression] [WS7(3)] [2009-11-21 10:22:47] [7d268329e554b8694908ba13e6e6f258]
-   PD          [Multiple Regression] [WS7(4)] [2009-11-21 10:55:20] [7d268329e554b8694908ba13e6e6f258]
- RMPD            [Univariate Data Series] [Niet-werkende wer...] [2009-11-25 19:16:52] [9717cb857c153ca3061376906953b329]
- RMP               [Univariate Explorative Data Analysis] [Univariate EDA] [2009-12-17 13:35:10] [9717cb857c153ca3061376906953b329]
-    D                [Univariate Explorative Data Analysis] [] [2010-12-16 18:32:59] [bcc4ad4a6c0f95d5b548de29638ac6c2]
- RMP                     [Variance Reduction Matrix] [] [2010-12-16 18:53:37] [4e3652732e77bb1a104cdb5f8d687d01] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
294912
293488
290555
284736
281818
287854
316263
325412
326011
328282
317480
317539
313737
312276
309391
302950
300316
304035
333476
337698
335932
323931
313927
314485
313218
309664
302963
298989
298423
301631
329765
335083
327616
309119
295916
291413
291542
284678
276475
272566
264981
263290
296806
303598
286994
276427
266424
267153
268381
262522
255542
253158
243803
250741
280445
285257
270976
261076
255603
260376
263903
264291
263276
262572
256167
264221
293860
300713
287224
275902
271115
277509
279681
276239
271037
266148
259497
266795
298305
303725
289742
276444
268606

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'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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=111185&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=111185&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111185&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'George Udny Yule' @ 72.249.76.132






Variance Reduction Matrix
V(Y[t],d=0,D=0)571598673.838084Range93895Trim Var.409941545.775495
V(Y[t],d=1,D=0)125742372.800964Range52013Trim Var.57780908.9194053
V(Y[t],d=2,D=0)164204232.652778Range61931Trim Var.90138274.5682093
V(Y[t],d=3,D=0)340432462.784652Range91364Trim Var.177914687.445814
V(Y[t],d=0,D=1)282801247.317103Range59458Trim Var.218254617.21659
V(Y[t],d=1,D=1)14585828.3817805Range22901Trim Var.6877573.91671074
V(Y[t],d=2,D=1)24875427.7791986Range29508Trim Var.8283119.0989071
V(Y[t],d=3,D=1)75758262.1755926Range50518Trim Var.29609701.2573446
V(Y[t],d=0,D=2)446943226.345412Range69734Trim Var.370682849.765602
V(Y[t],d=1,D=2)30365854.4370841Range24578Trim Var.17997107.1191554
V(Y[t],d=2,D=2)55682967.4686717Range40584Trim Var.28646014.2901961
V(Y[t],d=3,D=2)170949550.069805Range62099Trim Var.92436446.7710204

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 571598673.838084 & Range & 93895 & Trim Var. & 409941545.775495 \tabularnewline
V(Y[t],d=1,D=0) & 125742372.800964 & Range & 52013 & Trim Var. & 57780908.9194053 \tabularnewline
V(Y[t],d=2,D=0) & 164204232.652778 & Range & 61931 & Trim Var. & 90138274.5682093 \tabularnewline
V(Y[t],d=3,D=0) & 340432462.784652 & Range & 91364 & Trim Var. & 177914687.445814 \tabularnewline
V(Y[t],d=0,D=1) & 282801247.317103 & Range & 59458 & Trim Var. & 218254617.21659 \tabularnewline
V(Y[t],d=1,D=1) & 14585828.3817805 & Range & 22901 & Trim Var. & 6877573.91671074 \tabularnewline
V(Y[t],d=2,D=1) & 24875427.7791986 & Range & 29508 & Trim Var. & 8283119.0989071 \tabularnewline
V(Y[t],d=3,D=1) & 75758262.1755926 & Range & 50518 & Trim Var. & 29609701.2573446 \tabularnewline
V(Y[t],d=0,D=2) & 446943226.345412 & Range & 69734 & Trim Var. & 370682849.765602 \tabularnewline
V(Y[t],d=1,D=2) & 30365854.4370841 & Range & 24578 & Trim Var. & 17997107.1191554 \tabularnewline
V(Y[t],d=2,D=2) & 55682967.4686717 & Range & 40584 & Trim Var. & 28646014.2901961 \tabularnewline
V(Y[t],d=3,D=2) & 170949550.069805 & Range & 62099 & Trim Var. & 92436446.7710204 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=111185&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]571598673.838084[/C][C]Range[/C][C]93895[/C][C]Trim Var.[/C][C]409941545.775495[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]125742372.800964[/C][C]Range[/C][C]52013[/C][C]Trim Var.[/C][C]57780908.9194053[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]164204232.652778[/C][C]Range[/C][C]61931[/C][C]Trim Var.[/C][C]90138274.5682093[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]340432462.784652[/C][C]Range[/C][C]91364[/C][C]Trim Var.[/C][C]177914687.445814[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]282801247.317103[/C][C]Range[/C][C]59458[/C][C]Trim Var.[/C][C]218254617.21659[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]14585828.3817805[/C][C]Range[/C][C]22901[/C][C]Trim Var.[/C][C]6877573.91671074[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]24875427.7791986[/C][C]Range[/C][C]29508[/C][C]Trim Var.[/C][C]8283119.0989071[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]75758262.1755926[/C][C]Range[/C][C]50518[/C][C]Trim Var.[/C][C]29609701.2573446[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]446943226.345412[/C][C]Range[/C][C]69734[/C][C]Trim Var.[/C][C]370682849.765602[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]30365854.4370841[/C][C]Range[/C][C]24578[/C][C]Trim Var.[/C][C]17997107.1191554[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]55682967.4686717[/C][C]Range[/C][C]40584[/C][C]Trim Var.[/C][C]28646014.2901961[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]170949550.069805[/C][C]Range[/C][C]62099[/C][C]Trim Var.[/C][C]92436446.7710204[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=111185&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111185&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)571598673.838084Range93895Trim Var.409941545.775495
V(Y[t],d=1,D=0)125742372.800964Range52013Trim Var.57780908.9194053
V(Y[t],d=2,D=0)164204232.652778Range61931Trim Var.90138274.5682093
V(Y[t],d=3,D=0)340432462.784652Range91364Trim Var.177914687.445814
V(Y[t],d=0,D=1)282801247.317103Range59458Trim Var.218254617.21659
V(Y[t],d=1,D=1)14585828.3817805Range22901Trim Var.6877573.91671074
V(Y[t],d=2,D=1)24875427.7791986Range29508Trim Var.8283119.0989071
V(Y[t],d=3,D=1)75758262.1755926Range50518Trim Var.29609701.2573446
V(Y[t],d=0,D=2)446943226.345412Range69734Trim Var.370682849.765602
V(Y[t],d=1,D=2)30365854.4370841Range24578Trim Var.17997107.1191554
V(Y[t],d=2,D=2)55682967.4686717Range40584Trim Var.28646014.2901961
V(Y[t],d=3,D=2)170949550.069805Range62099Trim Var.92436446.7710204


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 2 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
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()