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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 computationSat, 22 Dec 2012 18:54:34 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/22/t135622048110dkdknhmftcnm9.htm/, Retrieved Tue, 23 Apr 2024 16:09:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=204648, Retrieved Tue, 23 Apr 2024 16:09:54 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact103

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [(Partial) Autocorrelation Function] [Identifying Integ...] [2009-11-22 12:16:10] [b98453cac15ba1066b407e146608df68]
-   PD        [(Partial) Autocorrelation Function] [Identifying Integ...] [2009-12-16 20:15:45] [1eab65e90adf64584b8e6f0da23ff414]
-   P           [(Partial) Autocorrelation Function] [Identifying Integ...] [2009-12-17 18:11:14] [1eab65e90adf64584b8e6f0da23ff414]
- RMP             [Variance Reduction Matrix] [Variance Reductio...] [2009-12-17 18:17:24] [1eab65e90adf64584b8e6f0da23ff414]
- R P                 [Variance Reduction Matrix] [] [2012-12-22 23:54:34] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
103.34
102.60
100.69
105.67
123.61
113.08
106.46
123.38
109.87
95.74
123.06
123.39
120.28
115.33
110.40
114.49
132.03
123.16
118.82
128.32
112.24
104.53
132.57
122.52
131.80
124.55
120.96
122.60
145.52
118.57
134.25
136.70
121.37
111.63
134.42
137.65
137.86
119.77
130.69
128.28
147.45
128.42
136.90
143.95
135.64
122.48
136.83
153.04
142.71
123.46
144.37
146.15
147.61
158.51
147.40
165.05
154.64
126.20
157.36
154.15
123.21
113.07
110.45
113.57
122.44
114.93
111.85
126.04
121.34
124.36

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' @ yule.wessa.net

\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' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=204648&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' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=204648&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=204648&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' @ yule.wessa.net






Variance Reduction Matrix
V(Y[t],d=0,D=0)237.813018964803Range69.31Trim Var.154.753575700687
V(Y[t],d=1,D=0)191.879169352089Range62.1Trim Var.119.291358251366
V(Y[t],d=2,D=0)513.743237225637Range109.47Trim Var.324.33606539548
V(Y[t],d=3,D=0)1562.49273206694Range186.47Trim Var.980.864144710696
V(Y[t],d=0,D=1)259.811391893527Range73.67Trim Var.156.26984841629
V(Y[t],d=1,D=1)137.290197932331Range54.99Trim Var.80.3967054901961
V(Y[t],d=2,D=1)388.271832435065Range97.1599999999999Trim Var.240.209355959184
V(Y[t],d=3,D=1)1307.36733784512Range176.87Trim Var.775.721361734694
V(Y[t],d=0,D=2)452.39654589372Range93.91Trim Var.233.075257435898
V(Y[t],d=1,D=2)325.331312828283Range95.0799999999999Trim Var.162.529615519568
V(Y[t],d=2,D=2)936.028294027484Range149.42Trim Var.535.045322332859
V(Y[t],d=3,D=2)3165.68345204872Range267.06Trim Var.1740.4674487988

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 237.813018964803 & Range & 69.31 & Trim Var. & 154.753575700687 \tabularnewline
V(Y[t],d=1,D=0) & 191.879169352089 & Range & 62.1 & Trim Var. & 119.291358251366 \tabularnewline
V(Y[t],d=2,D=0) & 513.743237225637 & Range & 109.47 & Trim Var. & 324.33606539548 \tabularnewline
V(Y[t],d=3,D=0) & 1562.49273206694 & Range & 186.47 & Trim Var. & 980.864144710696 \tabularnewline
V(Y[t],d=0,D=1) & 259.811391893527 & Range & 73.67 & Trim Var. & 156.26984841629 \tabularnewline
V(Y[t],d=1,D=1) & 137.290197932331 & Range & 54.99 & Trim Var. & 80.3967054901961 \tabularnewline
V(Y[t],d=2,D=1) & 388.271832435065 & Range & 97.1599999999999 & Trim Var. & 240.209355959184 \tabularnewline
V(Y[t],d=3,D=1) & 1307.36733784512 & Range & 176.87 & Trim Var. & 775.721361734694 \tabularnewline
V(Y[t],d=0,D=2) & 452.39654589372 & Range & 93.91 & Trim Var. & 233.075257435898 \tabularnewline
V(Y[t],d=1,D=2) & 325.331312828283 & Range & 95.0799999999999 & Trim Var. & 162.529615519568 \tabularnewline
V(Y[t],d=2,D=2) & 936.028294027484 & Range & 149.42 & Trim Var. & 535.045322332859 \tabularnewline
V(Y[t],d=3,D=2) & 3165.68345204872 & Range & 267.06 & Trim Var. & 1740.4674487988 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=204648&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]237.813018964803[/C][C]Range[/C][C]69.31[/C][C]Trim Var.[/C][C]154.753575700687[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]191.879169352089[/C][C]Range[/C][C]62.1[/C][C]Trim Var.[/C][C]119.291358251366[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]513.743237225637[/C][C]Range[/C][C]109.47[/C][C]Trim Var.[/C][C]324.33606539548[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]1562.49273206694[/C][C]Range[/C][C]186.47[/C][C]Trim Var.[/C][C]980.864144710696[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]259.811391893527[/C][C]Range[/C][C]73.67[/C][C]Trim Var.[/C][C]156.26984841629[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]137.290197932331[/C][C]Range[/C][C]54.99[/C][C]Trim Var.[/C][C]80.3967054901961[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]388.271832435065[/C][C]Range[/C][C]97.1599999999999[/C][C]Trim Var.[/C][C]240.209355959184[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]1307.36733784512[/C][C]Range[/C][C]176.87[/C][C]Trim Var.[/C][C]775.721361734694[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]452.39654589372[/C][C]Range[/C][C]93.91[/C][C]Trim Var.[/C][C]233.075257435898[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]325.331312828283[/C][C]Range[/C][C]95.0799999999999[/C][C]Trim Var.[/C][C]162.529615519568[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]936.028294027484[/C][C]Range[/C][C]149.42[/C][C]Trim Var.[/C][C]535.045322332859[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]3165.68345204872[/C][C]Range[/C][C]267.06[/C][C]Trim Var.[/C][C]1740.4674487988[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=204648&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=204648&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)237.813018964803Range69.31Trim Var.154.753575700687
V(Y[t],d=1,D=0)191.879169352089Range62.1Trim Var.119.291358251366
V(Y[t],d=2,D=0)513.743237225637Range109.47Trim Var.324.33606539548
V(Y[t],d=3,D=0)1562.49273206694Range186.47Trim Var.980.864144710696
V(Y[t],d=0,D=1)259.811391893527Range73.67Trim Var.156.26984841629
V(Y[t],d=1,D=1)137.290197932331Range54.99Trim Var.80.3967054901961
V(Y[t],d=2,D=1)388.271832435065Range97.1599999999999Trim Var.240.209355959184
V(Y[t],d=3,D=1)1307.36733784512Range176.87Trim Var.775.721361734694
V(Y[t],d=0,D=2)452.39654589372Range93.91Trim Var.233.075257435898
V(Y[t],d=1,D=2)325.331312828283Range95.0799999999999Trim Var.162.529615519568
V(Y[t],d=2,D=2)936.028294027484Range149.42Trim Var.535.045322332859
V(Y[t],d=3,D=2)3165.68345204872Range267.06Trim Var.1740.4674487988


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 50 ; par2 = 36 ;
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')