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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 computationMon, 22 Dec 2008 04:17:14 -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/22/t1229944666t6s0etkno40blq5.htm/, Retrieved Sun, 12 May 2024 22:57:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=36001, Retrieved Sun, 12 May 2024 22:57:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact206

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]
- R PD  [Univariate Data Series] [Tijdreeks 2 Buite...] [2008-12-11 16:25:30] [2d4aec5ed1856c4828162be37be304d9]
- RMP     [Central Tendency] [Central tendency ...] [2008-12-11 17:41:16] [2d4aec5ed1856c4828162be37be304d9]
- RMP       [Blocked Bootstrap Plot - Central Tendency] [Blocked Bootstrap...] [2008-12-12 08:14:08] [2d4aec5ed1856c4828162be37be304d9]
- RMP         [Tukey lambda PPCC Plot] [Tukey Lambda PPCC...] [2008-12-12 08:45:26] [2d4aec5ed1856c4828162be37be304d9]
- RMP           [Univariate Explorative Data Analysis] [Lag plot + ACF Ti...] [2008-12-12 08:54:04] [2d4aec5ed1856c4828162be37be304d9]
- RMP             [Variance Reduction Matrix] [VRM tijdreeks 2] [2008-12-12 10:58:24] [2d4aec5ed1856c4828162be37be304d9]
-    D                [Variance Reduction Matrix] [VRM Xt] [2008-12-22 11:17:14] [d7f41258beeebb8716e3f5d39f3cdc01] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
16283.6
16726.5
14968.9
14861
14583.3
15305.8
17903.9
16379.4
15420.3
17870.5
15912.8
13866.5
17823.2
17872
17420.4
16704.4
15991.2
16583.6
19123.5
17838.7
17209.4
18586.5
16258.1
15141.6
19202.1
17746.5
19090.1
18040.3
17515.5
17751.8
21072.4
17170
19439.5
19795.4
17574.9
16165.4
19464.6
19932.1
19961.2
17343.4
18924.2
18574.1
21350.6
18594.6
19823.1
20844.4
19640.2
17735.4
19813.6
22160
20664.3
17877.4
21211.2
21423.1
21688.7
23243.2
21490.2
22925.8
23184.8
18562.2

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'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36001&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36001&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36001&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Variance Reduction Matrix
V(Y[t],d=0,D=0)5069280.78724294Range9376.7Trim Var.3480817.41860238
V(Y[t],d=1,D=0)3896108.35026885Range8683.1Trim Var.2660506.33598694
V(Y[t],d=2,D=0)10208543.4146310Range13394.9Trim Var.7000632.74151961
V(Y[t],d=3,D=0)30708128.4316541Range24088Trim Var.21233111.5203294
V(Y[t],d=0,D=1)931617.362907802Range5345.5Trim Var.373280.527833914
V(Y[t],d=1,D=1)2161271.76098982Range7292Trim Var.1120332.82851219
V(Y[t],d=2,D=1)6883460.80754106Range14113.4Trim Var.3414840.79127564
V(Y[t],d=3,D=1)22816511.6894646Range24801.2Trim Var.10048409.3724831
V(Y[t],d=0,D=2)1526113.46046825Range5352.00000000001Trim Var.946142.293185485
V(Y[t],d=1,D=2)3183874.41193277Range7703.8Trim Var.1904559.39412903
V(Y[t],d=2,D=2)10214703.0550089Range13330.2Trim Var.5992871.82309195
V(Y[t],d=3,D=2)35273304.0643371Range26122.8Trim Var.20968476.0057881

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 5069280.78724294 & Range & 9376.7 & Trim Var. & 3480817.41860238 \tabularnewline
V(Y[t],d=1,D=0) & 3896108.35026885 & Range & 8683.1 & Trim Var. & 2660506.33598694 \tabularnewline
V(Y[t],d=2,D=0) & 10208543.4146310 & Range & 13394.9 & Trim Var. & 7000632.74151961 \tabularnewline
V(Y[t],d=3,D=0) & 30708128.4316541 & Range & 24088 & Trim Var. & 21233111.5203294 \tabularnewline
V(Y[t],d=0,D=1) & 931617.362907802 & Range & 5345.5 & Trim Var. & 373280.527833914 \tabularnewline
V(Y[t],d=1,D=1) & 2161271.76098982 & Range & 7292 & Trim Var. & 1120332.82851219 \tabularnewline
V(Y[t],d=2,D=1) & 6883460.80754106 & Range & 14113.4 & Trim Var. & 3414840.79127564 \tabularnewline
V(Y[t],d=3,D=1) & 22816511.6894646 & Range & 24801.2 & Trim Var. & 10048409.3724831 \tabularnewline
V(Y[t],d=0,D=2) & 1526113.46046825 & Range & 5352.00000000001 & Trim Var. & 946142.293185485 \tabularnewline
V(Y[t],d=1,D=2) & 3183874.41193277 & Range & 7703.8 & Trim Var. & 1904559.39412903 \tabularnewline
V(Y[t],d=2,D=2) & 10214703.0550089 & Range & 13330.2 & Trim Var. & 5992871.82309195 \tabularnewline
V(Y[t],d=3,D=2) & 35273304.0643371 & Range & 26122.8 & Trim Var. & 20968476.0057881 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36001&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]5069280.78724294[/C][C]Range[/C][C]9376.7[/C][C]Trim Var.[/C][C]3480817.41860238[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]3896108.35026885[/C][C]Range[/C][C]8683.1[/C][C]Trim Var.[/C][C]2660506.33598694[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]10208543.4146310[/C][C]Range[/C][C]13394.9[/C][C]Trim Var.[/C][C]7000632.74151961[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]30708128.4316541[/C][C]Range[/C][C]24088[/C][C]Trim Var.[/C][C]21233111.5203294[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]931617.362907802[/C][C]Range[/C][C]5345.5[/C][C]Trim Var.[/C][C]373280.527833914[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]2161271.76098982[/C][C]Range[/C][C]7292[/C][C]Trim Var.[/C][C]1120332.82851219[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]6883460.80754106[/C][C]Range[/C][C]14113.4[/C][C]Trim Var.[/C][C]3414840.79127564[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]22816511.6894646[/C][C]Range[/C][C]24801.2[/C][C]Trim Var.[/C][C]10048409.3724831[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]1526113.46046825[/C][C]Range[/C][C]5352.00000000001[/C][C]Trim Var.[/C][C]946142.293185485[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]3183874.41193277[/C][C]Range[/C][C]7703.8[/C][C]Trim Var.[/C][C]1904559.39412903[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]10214703.0550089[/C][C]Range[/C][C]13330.2[/C][C]Trim Var.[/C][C]5992871.82309195[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]35273304.0643371[/C][C]Range[/C][C]26122.8[/C][C]Trim Var.[/C][C]20968476.0057881[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36001&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36001&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)5069280.78724294Range9376.7Trim Var.3480817.41860238
V(Y[t],d=1,D=0)3896108.35026885Range8683.1Trim Var.2660506.33598694
V(Y[t],d=2,D=0)10208543.4146310Range13394.9Trim Var.7000632.74151961
V(Y[t],d=3,D=0)30708128.4316541Range24088Trim Var.21233111.5203294
V(Y[t],d=0,D=1)931617.362907802Range5345.5Trim Var.373280.527833914
V(Y[t],d=1,D=1)2161271.76098982Range7292Trim Var.1120332.82851219
V(Y[t],d=2,D=1)6883460.80754106Range14113.4Trim Var.3414840.79127564
V(Y[t],d=3,D=1)22816511.6894646Range24801.2Trim Var.10048409.3724831
V(Y[t],d=0,D=2)1526113.46046825Range5352.00000000001Trim Var.946142.293185485
V(Y[t],d=1,D=2)3183874.41193277Range7703.8Trim Var.1904559.39412903
V(Y[t],d=2,D=2)10214703.0550089Range13330.2Trim Var.5992871.82309195
V(Y[t],d=3,D=2)35273304.0643371Range26122.8Trim Var.20968476.0057881


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')