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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 07:53:11 -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/t1228229635mis2l91gmjwab0r.htm/, Retrieved Sun, 19 May 2024 11:10:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=27897, Retrieved Sun, 19 May 2024 11:10:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact207

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]
F RMPD    [Variance Reduction Matrix] [] [2008-12-02 14:53:11] [86e877ba38171644c8ca01af8044e645] [Current]
- RMP       [Standard Deviation-Mean Plot] [] [2008-12-09 14:02:49] [367e7d6b927a953ac0842a6750211350]
F RMP       [(Partial) Autocorrelation Function] [] [2008-12-09 14:06:56] [367e7d6b927a953ac0842a6750211350]
- RMP       [(Partial) Autocorrelation Function] [] [2008-12-09 14:09:41] [367e7d6b927a953ac0842a6750211350]
F RMP       [Spectral Analysis] [] [2008-12-09 14:12:25] [367e7d6b927a953ac0842a6750211350]
- RMP       [Spectral Analysis] [] [2008-12-09 14:14:32] [367e7d6b927a953ac0842a6750211350]
Feedback Forum
2008-12-07 13:27:23 [Käthe Vanderheggen] [reply] 
Dit is correct.
2008-12-16 09:08:42 [Katja van Hek] [reply] 
Dat klopt. VRM laat zien dat de variantie en de getrimde variantie het kleinst is bij d=0 en D=1. Hoe kleiner de variantie des te meer kun je verklaren aan de hand van dit model.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
45
24
18
20
22
39
55
35
38
47
1
57
50
33
19
2
7
15
56
53
24
48
2
49
46
32
37
10
8
16
55
46
46
45
6
45
52
44
35
15
44
51
58
23
44
43
6
51
53
47
19
18
38
43
23
43
18
43
6
31
49

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=27897&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=27897&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27897&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)289.015300546448Range57Trim Var.190.883265306122
V(Y[t],d=1,D=0)559.317514124294Range102Trim Var.374.978686233403
V(Y[t],d=2,D=0)1585.57276446522Range172Trim Var.1028.15602322206
V(Y[t],d=3,D=0)5289.22202056866Range328Trim Var.3364.31485671192
V(Y[t],d=0,D=1)191.545918367347Range71Trim Var.88.1107419712071
V(Y[t],d=1,D=1)350.836436170213Range101Trim Var.182.813008130081
V(Y[t],d=2,D=1)1047.88991674376Range183Trim Var.418.882051282051
V(Y[t],d=3,D=1)3509.86473429952Range356Trim Var.1444.66410256410
V(Y[t],d=0,D=2)457.022522522523Range86Trim Var.303.234848484848
V(Y[t],d=1,D=2)788.044444444444Range148Trim Var.320.279569892473
V(Y[t],d=2,D=2)2272.59327731092Range241Trim Var.972.898924731183
V(Y[t],d=3,D=2)7467.22370766488Range465Trim Var.2827.32068965517

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 289.015300546448 & Range & 57 & Trim Var. & 190.883265306122 \tabularnewline
V(Y[t],d=1,D=0) & 559.317514124294 & Range & 102 & Trim Var. & 374.978686233403 \tabularnewline
V(Y[t],d=2,D=0) & 1585.57276446522 & Range & 172 & Trim Var. & 1028.15602322206 \tabularnewline
V(Y[t],d=3,D=0) & 5289.22202056866 & Range & 328 & Trim Var. & 3364.31485671192 \tabularnewline
V(Y[t],d=0,D=1) & 191.545918367347 & Range & 71 & Trim Var. & 88.1107419712071 \tabularnewline
V(Y[t],d=1,D=1) & 350.836436170213 & Range & 101 & Trim Var. & 182.813008130081 \tabularnewline
V(Y[t],d=2,D=1) & 1047.88991674376 & Range & 183 & Trim Var. & 418.882051282051 \tabularnewline
V(Y[t],d=3,D=1) & 3509.86473429952 & Range & 356 & Trim Var. & 1444.66410256410 \tabularnewline
V(Y[t],d=0,D=2) & 457.022522522523 & Range & 86 & Trim Var. & 303.234848484848 \tabularnewline
V(Y[t],d=1,D=2) & 788.044444444444 & Range & 148 & Trim Var. & 320.279569892473 \tabularnewline
V(Y[t],d=2,D=2) & 2272.59327731092 & Range & 241 & Trim Var. & 972.898924731183 \tabularnewline
V(Y[t],d=3,D=2) & 7467.22370766488 & Range & 465 & Trim Var. & 2827.32068965517 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27897&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]289.015300546448[/C][C]Range[/C][C]57[/C][C]Trim Var.[/C][C]190.883265306122[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]559.317514124294[/C][C]Range[/C][C]102[/C][C]Trim Var.[/C][C]374.978686233403[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]1585.57276446522[/C][C]Range[/C][C]172[/C][C]Trim Var.[/C][C]1028.15602322206[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]5289.22202056866[/C][C]Range[/C][C]328[/C][C]Trim Var.[/C][C]3364.31485671192[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]191.545918367347[/C][C]Range[/C][C]71[/C][C]Trim Var.[/C][C]88.1107419712071[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]350.836436170213[/C][C]Range[/C][C]101[/C][C]Trim Var.[/C][C]182.813008130081[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]1047.88991674376[/C][C]Range[/C][C]183[/C][C]Trim Var.[/C][C]418.882051282051[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]3509.86473429952[/C][C]Range[/C][C]356[/C][C]Trim Var.[/C][C]1444.66410256410[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]457.022522522523[/C][C]Range[/C][C]86[/C][C]Trim Var.[/C][C]303.234848484848[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]788.044444444444[/C][C]Range[/C][C]148[/C][C]Trim Var.[/C][C]320.279569892473[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]2272.59327731092[/C][C]Range[/C][C]241[/C][C]Trim Var.[/C][C]972.898924731183[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]7467.22370766488[/C][C]Range[/C][C]465[/C][C]Trim Var.[/C][C]2827.32068965517[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27897&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27897&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)289.015300546448Range57Trim Var.190.883265306122
V(Y[t],d=1,D=0)559.317514124294Range102Trim Var.374.978686233403
V(Y[t],d=2,D=0)1585.57276446522Range172Trim Var.1028.15602322206
V(Y[t],d=3,D=0)5289.22202056866Range328Trim Var.3364.31485671192
V(Y[t],d=0,D=1)191.545918367347Range71Trim Var.88.1107419712071
V(Y[t],d=1,D=1)350.836436170213Range101Trim Var.182.813008130081
V(Y[t],d=2,D=1)1047.88991674376Range183Trim Var.418.882051282051
V(Y[t],d=3,D=1)3509.86473429952Range356Trim Var.1444.66410256410
V(Y[t],d=0,D=2)457.022522522523Range86Trim Var.303.234848484848
V(Y[t],d=1,D=2)788.044444444444Range148Trim Var.320.279569892473
V(Y[t],d=2,D=2)2272.59327731092Range241Trim Var.972.898924731183
V(Y[t],d=3,D=2)7467.22370766488Range465Trim Var.2827.32068965517


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')