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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 computationWed, 03 Dec 2008 06:37:20 -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/03/t1228311463azywxo7deo315ew.htm/, Retrieved Sun, 19 May 2024 03:08:57 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28701, Retrieved Sun, 19 May 2024 03:08:57 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsq8
Estimated Impact206

Tree of Dependent Computations

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]
- RMPD  [Standard Deviation-Mean Plot] [q5] [2008-12-03 13:15:06] [3ffd109c9e040b1ae7e5dbe576d4698c]
- RMPD    [(Partial) Autocorrelation Function] [q8] [2008-12-03 13:16:51] [3ffd109c9e040b1ae7e5dbe576d4698c]
- RMP       [Variance Reduction Matrix] [q8] [2008-12-03 13:29:02] [3ffd109c9e040b1ae7e5dbe576d4698c]
-    D          [Variance Reduction Matrix] [q8] [2008-12-03 13:37:20] [962e6c9020896982bc8283b8971710a9] [Current]
- RM              [(Partial) Autocorrelation Function] [q8] [2008-12-03 13:40:14] [3ffd109c9e040b1ae7e5dbe576d4698c]
- RM                [Spectral Analysis] [q8] [2008-12-03 13:42:10] [3ffd109c9e040b1ae7e5dbe576d4698c]
- RM D              [Cross Correlation Function] [q9] [2008-12-03 13:45:45] [3ffd109c9e040b1ae7e5dbe576d4698c]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
298427
289231
291975
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

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=28701&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=28701&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28701&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)563701642.827869Range93895Trim Var.371402145.783019
V(Y[t],d=1,D=0)121658464.796328Range52013Trim Var.63896365.4493361
V(Y[t],d=2,D=0)162476416.374635Range61931Trim Var.94800289.6386067
V(Y[t],d=3,D=0)355326537.803085Range91364Trim Var.179435923.373680
V(Y[t],d=0,D=1)365209069.960884Range70477Trim Var.261749604.244740
V(Y[t],d=1,D=1)17338388.679078Range22901Trim Var.7868909.75900116
V(Y[t],d=2,D=1)35354619.7141536Range29508Trim Var.14751530.8878049
V(Y[t],d=3,D=1)109297518.164734Range50518Trim Var.50913078.6660256
V(Y[t],d=0,D=2)305865324.971471Range61729Trim Var.221967541.541667
V(Y[t],d=1,D=2)36293796.9801587Range23620Trim Var.23583123.4798387
V(Y[t],d=2,D=2)79274773.8705882Range40584Trim Var.42988725.1612903
V(Y[t],d=3,D=2)227473630.667558Range62099Trim Var.142915122.529885

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 563701642.827869 & Range & 93895 & Trim Var. & 371402145.783019 \tabularnewline
V(Y[t],d=1,D=0) & 121658464.796328 & Range & 52013 & Trim Var. & 63896365.4493361 \tabularnewline
V(Y[t],d=2,D=0) & 162476416.374635 & Range & 61931 & Trim Var. & 94800289.6386067 \tabularnewline
V(Y[t],d=3,D=0) & 355326537.803085 & Range & 91364 & Trim Var. & 179435923.373680 \tabularnewline
V(Y[t],d=0,D=1) & 365209069.960884 & Range & 70477 & Trim Var. & 261749604.244740 \tabularnewline
V(Y[t],d=1,D=1) & 17338388.679078 & Range & 22901 & Trim Var. & 7868909.75900116 \tabularnewline
V(Y[t],d=2,D=1) & 35354619.7141536 & Range & 29508 & Trim Var. & 14751530.8878049 \tabularnewline
V(Y[t],d=3,D=1) & 109297518.164734 & Range & 50518 & Trim Var. & 50913078.6660256 \tabularnewline
V(Y[t],d=0,D=2) & 305865324.971471 & Range & 61729 & Trim Var. & 221967541.541667 \tabularnewline
V(Y[t],d=1,D=2) & 36293796.9801587 & Range & 23620 & Trim Var. & 23583123.4798387 \tabularnewline
V(Y[t],d=2,D=2) & 79274773.8705882 & Range & 40584 & Trim Var. & 42988725.1612903 \tabularnewline
V(Y[t],d=3,D=2) & 227473630.667558 & Range & 62099 & Trim Var. & 142915122.529885 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28701&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]563701642.827869[/C][C]Range[/C][C]93895[/C][C]Trim Var.[/C][C]371402145.783019[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]121658464.796328[/C][C]Range[/C][C]52013[/C][C]Trim Var.[/C][C]63896365.4493361[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]162476416.374635[/C][C]Range[/C][C]61931[/C][C]Trim Var.[/C][C]94800289.6386067[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]355326537.803085[/C][C]Range[/C][C]91364[/C][C]Trim Var.[/C][C]179435923.373680[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]365209069.960884[/C][C]Range[/C][C]70477[/C][C]Trim Var.[/C][C]261749604.244740[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]17338388.679078[/C][C]Range[/C][C]22901[/C][C]Trim Var.[/C][C]7868909.75900116[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]35354619.7141536[/C][C]Range[/C][C]29508[/C][C]Trim Var.[/C][C]14751530.8878049[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]109297518.164734[/C][C]Range[/C][C]50518[/C][C]Trim Var.[/C][C]50913078.6660256[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]305865324.971471[/C][C]Range[/C][C]61729[/C][C]Trim Var.[/C][C]221967541.541667[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]36293796.9801587[/C][C]Range[/C][C]23620[/C][C]Trim Var.[/C][C]23583123.4798387[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]79274773.8705882[/C][C]Range[/C][C]40584[/C][C]Trim Var.[/C][C]42988725.1612903[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]227473630.667558[/C][C]Range[/C][C]62099[/C][C]Trim Var.[/C][C]142915122.529885[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28701&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28701&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)563701642.827869Range93895Trim Var.371402145.783019
V(Y[t],d=1,D=0)121658464.796328Range52013Trim Var.63896365.4493361
V(Y[t],d=2,D=0)162476416.374635Range61931Trim Var.94800289.6386067
V(Y[t],d=3,D=0)355326537.803085Range91364Trim Var.179435923.373680
V(Y[t],d=0,D=1)365209069.960884Range70477Trim Var.261749604.244740
V(Y[t],d=1,D=1)17338388.679078Range22901Trim Var.7868909.75900116
V(Y[t],d=2,D=1)35354619.7141536Range29508Trim Var.14751530.8878049
V(Y[t],d=3,D=1)109297518.164734Range50518Trim Var.50913078.6660256
V(Y[t],d=0,D=2)305865324.971471Range61729Trim Var.221967541.541667
V(Y[t],d=1,D=2)36293796.9801587Range23620Trim Var.23583123.4798387
V(Y[t],d=2,D=2)79274773.8705882Range40584Trim Var.42988725.1612903
V(Y[t],d=3,D=2)227473630.667558Range62099Trim Var.142915122.529885


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')