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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 computationSat, 06 Dec 2008 05:44:59 -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/06/t1228567545i4fmvaftaok0kxd.htm/, Retrieved Sun, 19 May 2024 10:43:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=29552, Retrieved Sun, 19 May 2024 10:43:26 +0000
QR Codes:

Original text written by user:season op 6
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact213
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Run sequence plot...] [2008-12-02 22:19:27] [ed2ba3b6182103c15c0ab511ae4e6284]
- RMPD  [Standard Deviation-Mean Plot] [SD mean plot] [2008-12-06 11:49:39] [ed2ba3b6182103c15c0ab511ae4e6284]
F RM        [Variance Reduction Matrix] [variance reduction] [2008-12-06 12:44:59] [a8228479d4547a92e2d3f176a5299609] [Current]
F    D        [Variance Reduction Matrix] [VRM Vlaanderen] [2008-12-08 18:29:56] [077ffec662d24c06be4c491541a44245]
- RMPD        [(Partial) Autocorrelation Function] [ACF] [2008-12-08 18:32:31] [077ffec662d24c06be4c491541a44245]
-   P           [(Partial) Autocorrelation Function] [ACF] [2008-12-08 18:34:40] [077ffec662d24c06be4c491541a44245]
-   P             [(Partial) Autocorrelation Function] [ACF] [2008-12-08 18:36:48] [077ffec662d24c06be4c491541a44245]
-   P         [Variance Reduction Matrix] [variance reduction] [2008-12-08 19:33:22] [4ad596f10399a71ad29b7d76e6ab90ac]
-             [Variance Reduction Matrix] [variance reduction] [2008-12-09 00:17:49] [4ddbf81f78ea7c738951638c7e93f6ee]
-             [Variance Reduction Matrix] [] [2008-12-09 00:23:30] [29747f79f5beb5b2516e1271770ecb47]
Feedback Forum
2008-12-14 10:10:28 [Pieter Broos] [reply
berekening is correct, d=1 D=1 worden de differentiatiewaarden
2008-12-14 13:29:56 [Dana Molenberghs] [reply
De variantie is de spreiding na het differentieren. De variantie is hetgene dat nog verklaard moet worden. dus hoeveel te kleiner de variantie, hoeveel te beter. De variantie is hier klein in tegenstelling tot anderen. Dit is dus zeer goed.
2008-12-14 13:41:57 [Steven Hulsmans] [reply
De variantie is het kleinst bij V(Y[t],d=1,D=1), dus deze nemen we. Ook de trimmed variance is hiet het laagste.

Post a new message
Dataseries X:
92.66
94.2
94.37
94.45
94.62
94.37
93.43
94.79
94.88
94.79
94.62
94.71
93.77
95.73
95.99
95.82
95.47
95.82
94.71
96.33
96.5
96.16
96.33
96.33
95.05
96.84
96.92
97.44
97.78
97.69
96.67
98.29
98.2
98.71
98.54
98.2
96.92
99.06
99.65
99.82
99.99
100.33
99.31
101.1
101.1
100.93
100.85
100.93
99.6
101.88
101.81
102.38
102.74
102.82
101.72
103.47
102.98
102.68
102.9
103.03
101.29




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=29552&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=29552&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29552&T=0

As an alternative you can also use a 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)9.34143142076503Range10.81Trim Var.7.20808236574746
V(Y[t],d=1,D=0)0.823979971751413Range4.02Trim Var.0.519069375907111
V(Y[t],d=2,D=0)2.21213886616014Range5.96000000000001Trim Var.1.52677851959361
V(Y[t],d=3,D=0)7.1888050816697Range10.9800000000000Trim Var.5.10669573906485
V(Y[t],d=0,D=1)0.366903569023567Range2.81999999999999Trim Var.0.240029591836733
V(Y[t],d=1,D=1)0.145123270440252Range1.72999999999999Trim Var.0.084811100832563
V(Y[t],d=2,D=1)0.230296298984036Range1.97000000000001Trim Var.0.160934505087882
V(Y[t],d=3,D=1)0.655245060331829Range3.34000000000000Trim Var.0.449334347826092
V(Y[t],d=0,D=2)1.09449515306122Range4.69Trim Var.0.667758139534875
V(Y[t],d=1,D=2)0.440875886524825Range2.68999999999993Trim Var.0.303400000000005
V(Y[t],d=2,D=2)0.610395097132292Range2.97000000000008Trim Var.0.419129756097559
V(Y[t],d=3,D=2)1.71511541062804Range4.77Trim Var.1.21632506410260

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 9.34143142076503 & Range & 10.81 & Trim Var. & 7.20808236574746 \tabularnewline
V(Y[t],d=1,D=0) & 0.823979971751413 & Range & 4.02 & Trim Var. & 0.519069375907111 \tabularnewline
V(Y[t],d=2,D=0) & 2.21213886616014 & Range & 5.96000000000001 & Trim Var. & 1.52677851959361 \tabularnewline
V(Y[t],d=3,D=0) & 7.1888050816697 & Range & 10.9800000000000 & Trim Var. & 5.10669573906485 \tabularnewline
V(Y[t],d=0,D=1) & 0.366903569023567 & Range & 2.81999999999999 & Trim Var. & 0.240029591836733 \tabularnewline
V(Y[t],d=1,D=1) & 0.145123270440252 & Range & 1.72999999999999 & Trim Var. & 0.084811100832563 \tabularnewline
V(Y[t],d=2,D=1) & 0.230296298984036 & Range & 1.97000000000001 & Trim Var. & 0.160934505087882 \tabularnewline
V(Y[t],d=3,D=1) & 0.655245060331829 & Range & 3.34000000000000 & Trim Var. & 0.449334347826092 \tabularnewline
V(Y[t],d=0,D=2) & 1.09449515306122 & Range & 4.69 & Trim Var. & 0.667758139534875 \tabularnewline
V(Y[t],d=1,D=2) & 0.440875886524825 & Range & 2.68999999999993 & Trim Var. & 0.303400000000005 \tabularnewline
V(Y[t],d=2,D=2) & 0.610395097132292 & Range & 2.97000000000008 & Trim Var. & 0.419129756097559 \tabularnewline
V(Y[t],d=3,D=2) & 1.71511541062804 & Range & 4.77 & Trim Var. & 1.21632506410260 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29552&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]9.34143142076503[/C][C]Range[/C][C]10.81[/C][C]Trim Var.[/C][C]7.20808236574746[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]0.823979971751413[/C][C]Range[/C][C]4.02[/C][C]Trim Var.[/C][C]0.519069375907111[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]2.21213886616014[/C][C]Range[/C][C]5.96000000000001[/C][C]Trim Var.[/C][C]1.52677851959361[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]7.1888050816697[/C][C]Range[/C][C]10.9800000000000[/C][C]Trim Var.[/C][C]5.10669573906485[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]0.366903569023567[/C][C]Range[/C][C]2.81999999999999[/C][C]Trim Var.[/C][C]0.240029591836733[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.145123270440252[/C][C]Range[/C][C]1.72999999999999[/C][C]Trim Var.[/C][C]0.084811100832563[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]0.230296298984036[/C][C]Range[/C][C]1.97000000000001[/C][C]Trim Var.[/C][C]0.160934505087882[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]0.655245060331829[/C][C]Range[/C][C]3.34000000000000[/C][C]Trim Var.[/C][C]0.449334347826092[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]1.09449515306122[/C][C]Range[/C][C]4.69[/C][C]Trim Var.[/C][C]0.667758139534875[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]0.440875886524825[/C][C]Range[/C][C]2.68999999999993[/C][C]Trim Var.[/C][C]0.303400000000005[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]0.610395097132292[/C][C]Range[/C][C]2.97000000000008[/C][C]Trim Var.[/C][C]0.419129756097559[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]1.71511541062804[/C][C]Range[/C][C]4.77[/C][C]Trim Var.[/C][C]1.21632506410260[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29552&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29552&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Variance Reduction Matrix
V(Y[t],d=0,D=0)9.34143142076503Range10.81Trim Var.7.20808236574746
V(Y[t],d=1,D=0)0.823979971751413Range4.02Trim Var.0.519069375907111
V(Y[t],d=2,D=0)2.21213886616014Range5.96000000000001Trim Var.1.52677851959361
V(Y[t],d=3,D=0)7.1888050816697Range10.9800000000000Trim Var.5.10669573906485
V(Y[t],d=0,D=1)0.366903569023567Range2.81999999999999Trim Var.0.240029591836733
V(Y[t],d=1,D=1)0.145123270440252Range1.72999999999999Trim Var.0.084811100832563
V(Y[t],d=2,D=1)0.230296298984036Range1.97000000000001Trim Var.0.160934505087882
V(Y[t],d=3,D=1)0.655245060331829Range3.34000000000000Trim Var.0.449334347826092
V(Y[t],d=0,D=2)1.09449515306122Range4.69Trim Var.0.667758139534875
V(Y[t],d=1,D=2)0.440875886524825Range2.68999999999993Trim Var.0.303400000000005
V(Y[t],d=2,D=2)0.610395097132292Range2.97000000000008Trim Var.0.419129756097559
V(Y[t],d=3,D=2)1.71511541062804Range4.77Trim Var.1.21632506410260



Parameters (Session):
par1 = 6 ;
Parameters (R input):
par1 = 6 ;
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')