FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationTue, 21 Dec 2010 13:02:49 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/21/t1292936451qjoy6cxt5z2xgie.htm/, Retrieved Sun, 12 May 2024 03:29:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=113462, Retrieved Sun, 12 May 2024 03:29:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact143

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       [Spectral Analysis] [Identifying Integ...] [2009-11-22 12:38:17] [b98453cac15ba1066b407e146608df68]
-    D        [Spectral Analysis] [spectrumanalyse] [2009-11-28 09:48:21] [7773f496f69461f4a67891f0ef752622]
-   PD          [Spectral Analysis] [koffie en thee] [2009-12-16 20:15:20] [7773f496f69461f4a67891f0ef752622]
- RMPD            [Variance Reduction Matrix] [thee] [2009-12-16 20:39:57] [7773f496f69461f4a67891f0ef752622]
-    D              [Variance Reduction Matrix] [Appelen Jonagold ...] [2009-12-17 16:45:59] [7773f496f69461f4a67891f0ef752622]
-   P                 [Variance Reduction Matrix] [Appelen Golden va...] [2009-12-17 20:24:29] [7773f496f69461f4a67891f0ef752622]
-   PD                    [Variance Reduction Matrix] [VRMKoffie2] [2010-12-21 13:02:49] [9be3691a9b6ce074cb51fd18377fce28] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
7,14
7,24
7,33
7,61
7,66
7,69
7,7
7,68
7,71
7,71
7,72
7,68
7,72
7,74
7,76
7,9
7,97
7,96
7,95
7,97
7,93
7,99
7,96
7,92
7,97
7,98
8
8,04
8,17
8,29
8,26
8,3
8,32
8,28
8,27
8,32
8,31
8,34
8,32
8,36
8,33
8,35
8,34
8,37
8,31
8,33
8,34
8,25
8,27
8,31
8,25
8,3
8,3
8,35
8,78
8,9

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'George Udny Yule' @ 72.249.76.132

\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' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113462&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' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113462&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113462&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' @ 72.249.76.132






Variance Reduction Matrix
V(Y[t],d=0,D=0)0.120143344155844Range1.76Trim Var.0.0659489387755102
V(Y[t],d=1,D=0)0.0065237037037037Range0.52Trim Var.0.00176666666666667
V(Y[t],d=2,D=0)0.0100413696715583Range0.69Trim Var.0.00352748226950354
V(Y[t],d=3,D=0)0.0278827285921626Range1.02000000000000Trim Var.0.012182053654024
V(Y[t],d=0,D=1)0.0291663847780127Range0.65Trim Var.0.0190225462304410
V(Y[t],d=1,D=1)0.00896290143964563Range0.6Trim Var.0.0025313813813814
V(Y[t],d=2,D=1)0.0157417537746806Range0.759999999999998Trim Var.0.00653731092436972
V(Y[t],d=3,D=1)0.045205975609756Range1.17000000000000Trim Var.0.0228315966386554
V(Y[t],d=0,D=2)0.0560516129032259Range0.930000000000003Trim Var.0.0364109788359789
V(Y[t],d=1,D=2)0.0181122580645162Range0.650000000000001Trim Var.0.0088472934472935
V(Y[t],d=2,D=2)0.0330713793103448Range0.640000000000003Trim Var.0.0224721538461538
V(Y[t],d=3,D=2)0.099395320197044Range1.16000000000000Trim Var.0.068185666666666

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 0.120143344155844 & Range & 1.76 & Trim Var. & 0.0659489387755102 \tabularnewline
V(Y[t],d=1,D=0) & 0.0065237037037037 & Range & 0.52 & Trim Var. & 0.00176666666666667 \tabularnewline
V(Y[t],d=2,D=0) & 0.0100413696715583 & Range & 0.69 & Trim Var. & 0.00352748226950354 \tabularnewline
V(Y[t],d=3,D=0) & 0.0278827285921626 & Range & 1.02000000000000 & Trim Var. & 0.012182053654024 \tabularnewline
V(Y[t],d=0,D=1) & 0.0291663847780127 & Range & 0.65 & Trim Var. & 0.0190225462304410 \tabularnewline
V(Y[t],d=1,D=1) & 0.00896290143964563 & Range & 0.6 & Trim Var. & 0.0025313813813814 \tabularnewline
V(Y[t],d=2,D=1) & 0.0157417537746806 & Range & 0.759999999999998 & Trim Var. & 0.00653731092436972 \tabularnewline
V(Y[t],d=3,D=1) & 0.045205975609756 & Range & 1.17000000000000 & Trim Var. & 0.0228315966386554 \tabularnewline
V(Y[t],d=0,D=2) & 0.0560516129032259 & Range & 0.930000000000003 & Trim Var. & 0.0364109788359789 \tabularnewline
V(Y[t],d=1,D=2) & 0.0181122580645162 & Range & 0.650000000000001 & Trim Var. & 0.0088472934472935 \tabularnewline
V(Y[t],d=2,D=2) & 0.0330713793103448 & Range & 0.640000000000003 & Trim Var. & 0.0224721538461538 \tabularnewline
V(Y[t],d=3,D=2) & 0.099395320197044 & Range & 1.16000000000000 & Trim Var. & 0.068185666666666 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113462&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]0.120143344155844[/C][C]Range[/C][C]1.76[/C][C]Trim Var.[/C][C]0.0659489387755102[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]0.0065237037037037[/C][C]Range[/C][C]0.52[/C][C]Trim Var.[/C][C]0.00176666666666667[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]0.0100413696715583[/C][C]Range[/C][C]0.69[/C][C]Trim Var.[/C][C]0.00352748226950354[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]0.0278827285921626[/C][C]Range[/C][C]1.02000000000000[/C][C]Trim Var.[/C][C]0.012182053654024[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]0.0291663847780127[/C][C]Range[/C][C]0.65[/C][C]Trim Var.[/C][C]0.0190225462304410[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.00896290143964563[/C][C]Range[/C][C]0.6[/C][C]Trim Var.[/C][C]0.0025313813813814[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]0.0157417537746806[/C][C]Range[/C][C]0.759999999999998[/C][C]Trim Var.[/C][C]0.00653731092436972[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]0.045205975609756[/C][C]Range[/C][C]1.17000000000000[/C][C]Trim Var.[/C][C]0.0228315966386554[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]0.0560516129032259[/C][C]Range[/C][C]0.930000000000003[/C][C]Trim Var.[/C][C]0.0364109788359789[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]0.0181122580645162[/C][C]Range[/C][C]0.650000000000001[/C][C]Trim Var.[/C][C]0.0088472934472935[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]0.0330713793103448[/C][C]Range[/C][C]0.640000000000003[/C][C]Trim Var.[/C][C]0.0224721538461538[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]0.099395320197044[/C][C]Range[/C][C]1.16000000000000[/C][C]Trim Var.[/C][C]0.068185666666666[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113462&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113462&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)0.120143344155844Range1.76Trim Var.0.0659489387755102
V(Y[t],d=1,D=0)0.0065237037037037Range0.52Trim Var.0.00176666666666667
V(Y[t],d=2,D=0)0.0100413696715583Range0.69Trim Var.0.00352748226950354
V(Y[t],d=3,D=0)0.0278827285921626Range1.02000000000000Trim Var.0.012182053654024
V(Y[t],d=0,D=1)0.0291663847780127Range0.65Trim Var.0.0190225462304410
V(Y[t],d=1,D=1)0.00896290143964563Range0.6Trim Var.0.0025313813813814
V(Y[t],d=2,D=1)0.0157417537746806Range0.759999999999998Trim Var.0.00653731092436972
V(Y[t],d=3,D=1)0.045205975609756Range1.17000000000000Trim Var.0.0228315966386554
V(Y[t],d=0,D=2)0.0560516129032259Range0.930000000000003Trim Var.0.0364109788359789
V(Y[t],d=1,D=2)0.0181122580645162Range0.650000000000001Trim Var.0.0088472934472935
V(Y[t],d=2,D=2)0.0330713793103448Range0.640000000000003Trim Var.0.0224721538461538
V(Y[t],d=3,D=2)0.099395320197044Range1.16000000000000Trim Var.0.068185666666666


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')