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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, 27 Nov 2008 09:54:08 -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/Nov/27/t12278050552zra9scuno9g3ls.htm/, Retrieved Sun, 19 May 2024 03:50:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=25858, Retrieved Sun, 19 May 2024 03:50:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact198

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 18:40:39] [b98453cac15ba1066b407e146608df68]
F RM D    [Variance Reduction Matrix] [Q8 RVM Aantal ins...] [2008-11-27 16:54:08] [286e96bd53289970f8e5f25a93fb50b3] [Current]
F RMPD      [Cross Correlation Function] [] [2008-11-28 21:43:51] [819b576fab25b35cfda70f80599828ec]
-             [Cross Correlation Function] [] [2008-12-08 19:07:15] [888addc516c3b812dd7be4bd54caa358]
-             [Cross Correlation Function] [] [2008-12-09 08:28:08] [888addc516c3b812dd7be4bd54caa358]
- RMPD      [Cross Correlation Function] [Q7 CCF] [2008-11-28 21:49:23] [819b576fab25b35cfda70f80599828ec]
F   P         [Cross Correlation Function] [Cross Correlation Q7] [2008-12-01 11:34:07] [6fea0e9a9b3b29a63badf2c274e82506]
-               [Cross Correlation Function] [] [2008-12-08 18:59:41] [888addc516c3b812dd7be4bd54caa358]
-               [Cross Correlation Function] [] [2008-12-09 08:23:09] [888addc516c3b812dd7be4bd54caa358]
-   P       [Variance Reduction Matrix] [] [2008-12-09 08:25:33] [888addc516c3b812dd7be4bd54caa358]
Feedback Forum
2008-12-07 12:07:02 [Kevin Neelen] [reply] 
De variantie is het laagst bij d = 1 en D = 1. Dit betekent dat er origineel gezien seizoensinvloeden en een lineaire trend in de reeks vervat zaten.
2008-12-09 01:23:12 [Michael Van Spaandonck] [reply] 
Deze methode wordt gebruikt om te bepalen welke graad van differentiatie het beste is voor d en D.
De variantie is het laagst bij d = 1 en D = 1.
Dit betekent dat er origineel gezien seizoensinvloeden en een lineaire trend in de reeks vervat zaten.)

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
58.972
59.249
63.955
53.785
52.760
44.795
37.348
32.370
32.717
40.974
33.591
21.124
58.608
46.865
51.378
46.235
47.206
45.382
41.227
33.795
31.295
42.625
33.625
21.538
56.421
53.152
53.536
52.408
41.454
38.271
35.306
26.414
31.917
38.030
27.534
18.387
50.556
43.901
48.572
43.899
37.532
40.357
35.489
29.027
34.485
42.598
30.306
26.451
47.460
50.104
61.465
53.726
39.477
43.895
31.481
29.896
33.842
39.120
33.702
25.094

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=25858&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]0 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=25858&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=25858&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 time0 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Variance Reduction Matrix
V(Y[t],d=0,D=0)117.759454639548Range45.568Trim Var.82.7145996631726
V(Y[t],d=1,D=0)119.440020337230Range51.733Trim Var.49.8404042068215
V(Y[t],d=2,D=0)309.296106507259Range99.178Trim Var.114.281429856335
V(Y[t],d=3,D=0)977.452055833333Range164.661Trim Var.425.129005683137
V(Y[t],d=0,D=1)30.3596362819149Range25.47Trim Var.17.1522691196283
V(Y[t],d=1,D=1)27.2287549398705Range21.319Trim Var.15.4322286219512
V(Y[t],d=2,D=1)69.3248663772947Range36.911Trim Var.43.7640628076923
V(Y[t],d=3,D=1)219.532120436364Range60.995Trim Var.142.409416178138
V(Y[t],d=0,D=2)90.0480208349206Range34.209Trim Var.65.2050575554435
V(Y[t],d=1,D=2)67.0215870218487Range34.415Trim Var.40.9253795892473
V(Y[t],d=2,D=2)150.540902289661Range48.502Trim Var.102.470137489655
V(Y[t],d=3,D=2)459.397272590909Range76.3Trim Var.344.80274523399

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 117.759454639548 & Range & 45.568 & Trim Var. & 82.7145996631726 \tabularnewline
V(Y[t],d=1,D=0) & 119.440020337230 & Range & 51.733 & Trim Var. & 49.8404042068215 \tabularnewline
V(Y[t],d=2,D=0) & 309.296106507259 & Range & 99.178 & Trim Var. & 114.281429856335 \tabularnewline
V(Y[t],d=3,D=0) & 977.452055833333 & Range & 164.661 & Trim Var. & 425.129005683137 \tabularnewline
V(Y[t],d=0,D=1) & 30.3596362819149 & Range & 25.47 & Trim Var. & 17.1522691196283 \tabularnewline
V(Y[t],d=1,D=1) & 27.2287549398705 & Range & 21.319 & Trim Var. & 15.4322286219512 \tabularnewline
V(Y[t],d=2,D=1) & 69.3248663772947 & Range & 36.911 & Trim Var. & 43.7640628076923 \tabularnewline
V(Y[t],d=3,D=1) & 219.532120436364 & Range & 60.995 & Trim Var. & 142.409416178138 \tabularnewline
V(Y[t],d=0,D=2) & 90.0480208349206 & Range & 34.209 & Trim Var. & 65.2050575554435 \tabularnewline
V(Y[t],d=1,D=2) & 67.0215870218487 & Range & 34.415 & Trim Var. & 40.9253795892473 \tabularnewline
V(Y[t],d=2,D=2) & 150.540902289661 & Range & 48.502 & Trim Var. & 102.470137489655 \tabularnewline
V(Y[t],d=3,D=2) & 459.397272590909 & Range & 76.3 & Trim Var. & 344.80274523399 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=25858&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]117.759454639548[/C][C]Range[/C][C]45.568[/C][C]Trim Var.[/C][C]82.7145996631726[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]119.440020337230[/C][C]Range[/C][C]51.733[/C][C]Trim Var.[/C][C]49.8404042068215[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]309.296106507259[/C][C]Range[/C][C]99.178[/C][C]Trim Var.[/C][C]114.281429856335[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]977.452055833333[/C][C]Range[/C][C]164.661[/C][C]Trim Var.[/C][C]425.129005683137[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]30.3596362819149[/C][C]Range[/C][C]25.47[/C][C]Trim Var.[/C][C]17.1522691196283[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]27.2287549398705[/C][C]Range[/C][C]21.319[/C][C]Trim Var.[/C][C]15.4322286219512[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]69.3248663772947[/C][C]Range[/C][C]36.911[/C][C]Trim Var.[/C][C]43.7640628076923[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]219.532120436364[/C][C]Range[/C][C]60.995[/C][C]Trim Var.[/C][C]142.409416178138[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]90.0480208349206[/C][C]Range[/C][C]34.209[/C][C]Trim Var.[/C][C]65.2050575554435[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]67.0215870218487[/C][C]Range[/C][C]34.415[/C][C]Trim Var.[/C][C]40.9253795892473[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]150.540902289661[/C][C]Range[/C][C]48.502[/C][C]Trim Var.[/C][C]102.470137489655[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]459.397272590909[/C][C]Range[/C][C]76.3[/C][C]Trim Var.[/C][C]344.80274523399[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=25858&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=25858&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)117.759454639548Range45.568Trim Var.82.7145996631726
V(Y[t],d=1,D=0)119.440020337230Range51.733Trim Var.49.8404042068215
V(Y[t],d=2,D=0)309.296106507259Range99.178Trim Var.114.281429856335
V(Y[t],d=3,D=0)977.452055833333Range164.661Trim Var.425.129005683137
V(Y[t],d=0,D=1)30.3596362819149Range25.47Trim Var.17.1522691196283
V(Y[t],d=1,D=1)27.2287549398705Range21.319Trim Var.15.4322286219512
V(Y[t],d=2,D=1)69.3248663772947Range36.911Trim Var.43.7640628076923
V(Y[t],d=3,D=1)219.532120436364Range60.995Trim Var.142.409416178138
V(Y[t],d=0,D=2)90.0480208349206Range34.209Trim Var.65.2050575554435
V(Y[t],d=1,D=2)67.0215870218487Range34.415Trim Var.40.9253795892473
V(Y[t],d=2,D=2)150.540902289661Range48.502Trim Var.102.470137489655
V(Y[t],d=3,D=2)459.397272590909Range76.3Trim Var.344.80274523399


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 500 ; par2 = 0.5 ;
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')