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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 06:29:02 -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/t1228311005esk3jjjfgnyugnk.htm/, Retrieved Sun, 19 May 2024 06:06:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28695, Retrieved Sun, 19 May 2024 06:06:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsq8
Estimated Impact209

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] [962e6c9020896982bc8283b8971710a9] [Current]
-    D          [Variance Reduction Matrix] [q8] [2008-12-03 13:37:20] [3ffd109c9e040b1ae7e5dbe576d4698c]
- 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 
267037
258113
262813
267413
267366
264777
258863
254844
254868
277267
285351
286602
283042
276687
277915
277128
277103
275037
270150
267140
264993
287259
291186
292300
288186
281477
282656
280190
280408
276836
275216
274352
271311
289802
290726
292300
278506
269826
265861
269034
264176
255198
253353
246057
235372
258556
260993
254663
250643
243422
247105
248541
245039
237080
237085
225554
226839
247934
248333
246969
245098

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'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=28695&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=28695&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28695&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'Gwilym Jenkins' @ 72.249.127.135






Variance Reduction Matrix
V(Y[t],d=0,D=0)294581710.532240Range66746Trim Var.194677047.283019
V(Y[t],d=1,D=0)62465285.1805085Range36978Trim Var.31462669.3081761
V(Y[t],d=2,D=0)111910925.424898Range54616Trim Var.58639354.4753266
V(Y[t],d=3,D=0)299924590.305203Range91874Trim Var.158354509.209653
V(Y[t],d=0,D=1)234403433.84949Range56211Trim Var.171080390.766334
V(Y[t],d=1,D=1)18499405.7429078Range21650Trim Var.8573019.5029036
V(Y[t],d=2,D=1)42922784.4523589Range31737Trim Var.20712415.45
V(Y[t],d=3,D=1)139023269.458937Range57359Trim Var.67904366.2916667
V(Y[t],d=0,D=2)303086903.114114Range72200Trim Var.192128020.801136
V(Y[t],d=1,D=2)54283943.3801587Range28740Trim Var.32455538.1764113
V(Y[t],d=2,D=2)131765687.878992Range54214Trim Var.76212630.6645161
V(Y[t],d=3,D=2)413631120.375223Range84540Trim Var.241800597.586207

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 294581710.532240 & Range & 66746 & Trim Var. & 194677047.283019 \tabularnewline
V(Y[t],d=1,D=0) & 62465285.1805085 & Range & 36978 & Trim Var. & 31462669.3081761 \tabularnewline
V(Y[t],d=2,D=0) & 111910925.424898 & Range & 54616 & Trim Var. & 58639354.4753266 \tabularnewline
V(Y[t],d=3,D=0) & 299924590.305203 & Range & 91874 & Trim Var. & 158354509.209653 \tabularnewline
V(Y[t],d=0,D=1) & 234403433.84949 & Range & 56211 & Trim Var. & 171080390.766334 \tabularnewline
V(Y[t],d=1,D=1) & 18499405.7429078 & Range & 21650 & Trim Var. & 8573019.5029036 \tabularnewline
V(Y[t],d=2,D=1) & 42922784.4523589 & Range & 31737 & Trim Var. & 20712415.45 \tabularnewline
V(Y[t],d=3,D=1) & 139023269.458937 & Range & 57359 & Trim Var. & 67904366.2916667 \tabularnewline
V(Y[t],d=0,D=2) & 303086903.114114 & Range & 72200 & Trim Var. & 192128020.801136 \tabularnewline
V(Y[t],d=1,D=2) & 54283943.3801587 & Range & 28740 & Trim Var. & 32455538.1764113 \tabularnewline
V(Y[t],d=2,D=2) & 131765687.878992 & Range & 54214 & Trim Var. & 76212630.6645161 \tabularnewline
V(Y[t],d=3,D=2) & 413631120.375223 & Range & 84540 & Trim Var. & 241800597.586207 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28695&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]294581710.532240[/C][C]Range[/C][C]66746[/C][C]Trim Var.[/C][C]194677047.283019[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]62465285.1805085[/C][C]Range[/C][C]36978[/C][C]Trim Var.[/C][C]31462669.3081761[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]111910925.424898[/C][C]Range[/C][C]54616[/C][C]Trim Var.[/C][C]58639354.4753266[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]299924590.305203[/C][C]Range[/C][C]91874[/C][C]Trim Var.[/C][C]158354509.209653[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]234403433.84949[/C][C]Range[/C][C]56211[/C][C]Trim Var.[/C][C]171080390.766334[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]18499405.7429078[/C][C]Range[/C][C]21650[/C][C]Trim Var.[/C][C]8573019.5029036[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]42922784.4523589[/C][C]Range[/C][C]31737[/C][C]Trim Var.[/C][C]20712415.45[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]139023269.458937[/C][C]Range[/C][C]57359[/C][C]Trim Var.[/C][C]67904366.2916667[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]303086903.114114[/C][C]Range[/C][C]72200[/C][C]Trim Var.[/C][C]192128020.801136[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]54283943.3801587[/C][C]Range[/C][C]28740[/C][C]Trim Var.[/C][C]32455538.1764113[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]131765687.878992[/C][C]Range[/C][C]54214[/C][C]Trim Var.[/C][C]76212630.6645161[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]413631120.375223[/C][C]Range[/C][C]84540[/C][C]Trim Var.[/C][C]241800597.586207[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28695&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28695&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)294581710.532240Range66746Trim Var.194677047.283019
V(Y[t],d=1,D=0)62465285.1805085Range36978Trim Var.31462669.3081761
V(Y[t],d=2,D=0)111910925.424898Range54616Trim Var.58639354.4753266
V(Y[t],d=3,D=0)299924590.305203Range91874Trim Var.158354509.209653
V(Y[t],d=0,D=1)234403433.84949Range56211Trim Var.171080390.766334
V(Y[t],d=1,D=1)18499405.7429078Range21650Trim Var.8573019.5029036
V(Y[t],d=2,D=1)42922784.4523589Range31737Trim Var.20712415.45
V(Y[t],d=3,D=1)139023269.458937Range57359Trim Var.67904366.2916667
V(Y[t],d=0,D=2)303086903.114114Range72200Trim Var.192128020.801136
V(Y[t],d=1,D=2)54283943.3801587Range28740Trim Var.32455538.1764113
V(Y[t],d=2,D=2)131765687.878992Range54214Trim Var.76212630.6645161
V(Y[t],d=3,D=2)413631120.375223Range84540Trim Var.241800597.586207


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')