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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_variancereduction.wasp
Title produced by softwareVariance Reduction Matrix
Date of computationTue, 02 Dec 2008 07:50:00 -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/02/t12282294383t9dpp8o1luumv3.htm/, Retrieved Sun, 19 May 2024 12:17:12 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=27885, Retrieved Sun, 19 May 2024 12:17:12 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordskleuter
Estimated Impact168

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Law of Averages] [Random Walk Simul...] [2008-11-25 17:50:19] [b98453cac15ba1066b407e146608df68]
F RMPD    [Variance Reduction Matrix] [] [2008-12-02 14:50:00] [c233791e22ae82ed03fa45b0d63a2757] [Current]
Feedback Forum
2008-12-03 19:56:36 [407693b66d7f2e0b350979005057872d] [reply] 
Dit antwoord is volledig juist. Grafiek: typisch fenomeen
onderzoeken of ere en verband is tussen Yt en Xt , maar de correlatie kan vertekend zijn door Zt , een variabele die invloed heeft op Yt en Xt.
2008-12-06 11:20:09 [Käthe Vanderheggen] [reply] 
Dit is juist. d=1, D=1 geeft ook voor de getrimde variantie de kleinste waarde.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
569
580
578
565
547
555
562
561
555
544
537
543
594
611
613
611
594
595
591
589
584
573
567
569
621
629
628
612
595
597
593
590
580
574
573
573
620
626
620
588
566
557
561
549
532
526
511
499
555
565
542
527
510
514
517
508
493
490
469
478
528

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=27885&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=27885&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27885&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)1555.51639344262Range160Trim Var.978.214078374456
V(Y[t],d=1,D=0)342.118361581921Range88Trim Var.178.393081761006
V(Y[t],d=2,D=0)479.986557568673Range114Trim Var.246.125544267054
V(Y[t],d=3,D=0)1103.25831820932Range179Trim Var.470.851809954751
V(Y[t],d=0,D=1)1260.80782312925Range125Trim Var.950.854928017719
V(Y[t],d=1,D=1)65.3120567375886Range38Trim Var.31.1743902439024
V(Y[t],d=2,D=1)135.629047178538Range61Trim Var.60.9121951219512
V(Y[t],d=3,D=1)413.764734299517Range109Trim Var.176.603238866397
V(Y[t],d=0,D=2)804.478978978979Range131Trim Var.436.484848484848
V(Y[t],d=1,D=2)166.971428571429Range58Trim Var.87.4153225806452
V(Y[t],d=2,D=2)321.470588235294Range93Trim Var.162.769892473118
V(Y[t],d=3,D=2)922.477718360071Range136Trim Var.471.098850574713

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 1555.51639344262 & Range & 160 & Trim Var. & 978.214078374456 \tabularnewline
V(Y[t],d=1,D=0) & 342.118361581921 & Range & 88 & Trim Var. & 178.393081761006 \tabularnewline
V(Y[t],d=2,D=0) & 479.986557568673 & Range & 114 & Trim Var. & 246.125544267054 \tabularnewline
V(Y[t],d=3,D=0) & 1103.25831820932 & Range & 179 & Trim Var. & 470.851809954751 \tabularnewline
V(Y[t],d=0,D=1) & 1260.80782312925 & Range & 125 & Trim Var. & 950.854928017719 \tabularnewline
V(Y[t],d=1,D=1) & 65.3120567375886 & Range & 38 & Trim Var. & 31.1743902439024 \tabularnewline
V(Y[t],d=2,D=1) & 135.629047178538 & Range & 61 & Trim Var. & 60.9121951219512 \tabularnewline
V(Y[t],d=3,D=1) & 413.764734299517 & Range & 109 & Trim Var. & 176.603238866397 \tabularnewline
V(Y[t],d=0,D=2) & 804.478978978979 & Range & 131 & Trim Var. & 436.484848484848 \tabularnewline
V(Y[t],d=1,D=2) & 166.971428571429 & Range & 58 & Trim Var. & 87.4153225806452 \tabularnewline
V(Y[t],d=2,D=2) & 321.470588235294 & Range & 93 & Trim Var. & 162.769892473118 \tabularnewline
V(Y[t],d=3,D=2) & 922.477718360071 & Range & 136 & Trim Var. & 471.098850574713 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27885&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]1555.51639344262[/C][C]Range[/C][C]160[/C][C]Trim Var.[/C][C]978.214078374456[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]342.118361581921[/C][C]Range[/C][C]88[/C][C]Trim Var.[/C][C]178.393081761006[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]479.986557568673[/C][C]Range[/C][C]114[/C][C]Trim Var.[/C][C]246.125544267054[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]1103.25831820932[/C][C]Range[/C][C]179[/C][C]Trim Var.[/C][C]470.851809954751[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]1260.80782312925[/C][C]Range[/C][C]125[/C][C]Trim Var.[/C][C]950.854928017719[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]65.3120567375886[/C][C]Range[/C][C]38[/C][C]Trim Var.[/C][C]31.1743902439024[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]135.629047178538[/C][C]Range[/C][C]61[/C][C]Trim Var.[/C][C]60.9121951219512[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]413.764734299517[/C][C]Range[/C][C]109[/C][C]Trim Var.[/C][C]176.603238866397[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]804.478978978979[/C][C]Range[/C][C]131[/C][C]Trim Var.[/C][C]436.484848484848[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]166.971428571429[/C][C]Range[/C][C]58[/C][C]Trim Var.[/C][C]87.4153225806452[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]321.470588235294[/C][C]Range[/C][C]93[/C][C]Trim Var.[/C][C]162.769892473118[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]922.477718360071[/C][C]Range[/C][C]136[/C][C]Trim Var.[/C][C]471.098850574713[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27885&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27885&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)1555.51639344262Range160Trim Var.978.214078374456
V(Y[t],d=1,D=0)342.118361581921Range88Trim Var.178.393081761006
V(Y[t],d=2,D=0)479.986557568673Range114Trim Var.246.125544267054
V(Y[t],d=3,D=0)1103.25831820932Range179Trim Var.470.851809954751
V(Y[t],d=0,D=1)1260.80782312925Range125Trim Var.950.854928017719
V(Y[t],d=1,D=1)65.3120567375886Range38Trim Var.31.1743902439024
V(Y[t],d=2,D=1)135.629047178538Range61Trim Var.60.9121951219512
V(Y[t],d=3,D=1)413.764734299517Range109Trim Var.176.603238866397
V(Y[t],d=0,D=2)804.478978978979Range131Trim Var.436.484848484848
V(Y[t],d=1,D=2)166.971428571429Range58Trim Var.87.4153225806452
V(Y[t],d=2,D=2)321.470588235294Range93Trim Var.162.769892473118
V(Y[t],d=3,D=2)922.477718360071Range136Trim Var.471.098850574713


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')