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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, 09 Dec 2008 06:36:33 -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/09/t12288298227mumsyeb2d0r4uh.htm/, Retrieved Fri, 17 May 2024 02:40:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31377, Retrieved Fri, 17 May 2024 02:40:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact175

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Variance Reduction Matrix] [] [2008-12-09 13:36:33] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
108.9
110.5
111.0
110.7
110.0
111.4
107.7
110.4
110.5
106.4
107.5
108.8
107.1
107.9
107.2
106.3
106.7
105.4
109.4
106.7
105.2
107.0
105.4
106.1
105.8
104.2
102.7
102.7
104.9
102.3
104.0
101.2
102.2
101.4
101.1
97.2
99.7
99.4
98.0
103.1
99.4
100.8
96.4
99.7
100.9
101.3
102.6
105.6
107.2
104.0
108.7
104.9
105.3
105.0
106.1
103.7
102.1
97.2
99.5
102.9

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=31377&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=31377&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31377&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)14.7191073446328Range15Trim Var.10.6944968553459
V(Y[t],d=1,D=0)5.52741087083576Range9.99999999999999Trim Var.3.77206095791001
V(Y[t],d=2,D=0)15.8863883847550Range16.7Trim Var.10.5350377073906
V(Y[t],d=3,D=0)54.7116979949874Range30.3000000000000Trim Var.37.5896078431372
V(Y[t],d=0,D=1)20.3106382978723Range19.6Trim Var.11.3923112659698
V(Y[t],d=1,D=1)14.2881036077706Range16.6Trim Var.9.04795121951217
V(Y[t],d=2,D=1)44.2761932367149Range28.0000000000000Trim Var.26.7643525641025
V(Y[t],d=3,D=1)158.512252525252Range52Trim Var.98.0999999999996
V(Y[t],d=0,D=2)46.2850396825396Range28.4000000000000Trim Var.28.8949899193548
V(Y[t],d=1,D=2)39.4892773109243Range25.6000000000000Trim Var.24.7291612903225
V(Y[t],d=2,D=2)124.480721925133Range47.3999999999999Trim Var.78.8089195402296
V(Y[t],d=3,D=2)460.929962121211Range84.6999999999999Trim Var.303.334704433496

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 14.7191073446328 & Range & 15 & Trim Var. & 10.6944968553459 \tabularnewline
V(Y[t],d=1,D=0) & 5.52741087083576 & Range & 9.99999999999999 & Trim Var. & 3.77206095791001 \tabularnewline
V(Y[t],d=2,D=0) & 15.8863883847550 & Range & 16.7 & Trim Var. & 10.5350377073906 \tabularnewline
V(Y[t],d=3,D=0) & 54.7116979949874 & Range & 30.3000000000000 & Trim Var. & 37.5896078431372 \tabularnewline
V(Y[t],d=0,D=1) & 20.3106382978723 & Range & 19.6 & Trim Var. & 11.3923112659698 \tabularnewline
V(Y[t],d=1,D=1) & 14.2881036077706 & Range & 16.6 & Trim Var. & 9.04795121951217 \tabularnewline
V(Y[t],d=2,D=1) & 44.2761932367149 & Range & 28.0000000000000 & Trim Var. & 26.7643525641025 \tabularnewline
V(Y[t],d=3,D=1) & 158.512252525252 & Range & 52 & Trim Var. & 98.0999999999996 \tabularnewline
V(Y[t],d=0,D=2) & 46.2850396825396 & Range & 28.4000000000000 & Trim Var. & 28.8949899193548 \tabularnewline
V(Y[t],d=1,D=2) & 39.4892773109243 & Range & 25.6000000000000 & Trim Var. & 24.7291612903225 \tabularnewline
V(Y[t],d=2,D=2) & 124.480721925133 & Range & 47.3999999999999 & Trim Var. & 78.8089195402296 \tabularnewline
V(Y[t],d=3,D=2) & 460.929962121211 & Range & 84.6999999999999 & Trim Var. & 303.334704433496 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31377&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]14.7191073446328[/C][C]Range[/C][C]15[/C][C]Trim Var.[/C][C]10.6944968553459[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]5.52741087083576[/C][C]Range[/C][C]9.99999999999999[/C][C]Trim Var.[/C][C]3.77206095791001[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]15.8863883847550[/C][C]Range[/C][C]16.7[/C][C]Trim Var.[/C][C]10.5350377073906[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]54.7116979949874[/C][C]Range[/C][C]30.3000000000000[/C][C]Trim Var.[/C][C]37.5896078431372[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]20.3106382978723[/C][C]Range[/C][C]19.6[/C][C]Trim Var.[/C][C]11.3923112659698[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]14.2881036077706[/C][C]Range[/C][C]16.6[/C][C]Trim Var.[/C][C]9.04795121951217[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]44.2761932367149[/C][C]Range[/C][C]28.0000000000000[/C][C]Trim Var.[/C][C]26.7643525641025[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]158.512252525252[/C][C]Range[/C][C]52[/C][C]Trim Var.[/C][C]98.0999999999996[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]46.2850396825396[/C][C]Range[/C][C]28.4000000000000[/C][C]Trim Var.[/C][C]28.8949899193548[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]39.4892773109243[/C][C]Range[/C][C]25.6000000000000[/C][C]Trim Var.[/C][C]24.7291612903225[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]124.480721925133[/C][C]Range[/C][C]47.3999999999999[/C][C]Trim Var.[/C][C]78.8089195402296[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]460.929962121211[/C][C]Range[/C][C]84.6999999999999[/C][C]Trim Var.[/C][C]303.334704433496[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31377&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31377&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)14.7191073446328Range15Trim Var.10.6944968553459
V(Y[t],d=1,D=0)5.52741087083576Range9.99999999999999Trim Var.3.77206095791001
V(Y[t],d=2,D=0)15.8863883847550Range16.7Trim Var.10.5350377073906
V(Y[t],d=3,D=0)54.7116979949874Range30.3000000000000Trim Var.37.5896078431372
V(Y[t],d=0,D=1)20.3106382978723Range19.6Trim Var.11.3923112659698
V(Y[t],d=1,D=1)14.2881036077706Range16.6Trim Var.9.04795121951217
V(Y[t],d=2,D=1)44.2761932367149Range28.0000000000000Trim Var.26.7643525641025
V(Y[t],d=3,D=1)158.512252525252Range52Trim Var.98.0999999999996
V(Y[t],d=0,D=2)46.2850396825396Range28.4000000000000Trim Var.28.8949899193548
V(Y[t],d=1,D=2)39.4892773109243Range25.6000000000000Trim Var.24.7291612903225
V(Y[t],d=2,D=2)124.480721925133Range47.3999999999999Trim Var.78.8089195402296
V(Y[t],d=3,D=2)460.929962121211Range84.6999999999999Trim Var.303.334704433496


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')