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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_rwalk.wasp
Title produced by softwareLaw of Averages
Date of computationMon, 01 Dec 2008 09:59:28 -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/01/t1228150805ow91q8p063xf9bp.htm/, Retrieved Sun, 05 May 2024 16:06:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=26993, Retrieved Sun, 05 May 2024 16:06:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact181

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Law of Averages] [Random Walk Simul...] [2008-11-25 18:31:28] [b98453cac15ba1066b407e146608df68]
F         [Law of Averages] [Non Stationary Ti...] [2008-12-01 16:59:28] [620b6ad5c4696049e39cb73ce029682c] [Current]
Feedback Forum
2008-12-08 09:23:53 [256f97d8b7c07ed49f142eff724c6520] [reply] 
Bijna correct, aanvulling
d = het aantal keer dat de reeks niet-seizoenaal gedifferentieerd is.
D = het aantal keer dat de reeks seizoenaal gedifferentieer is.
Maar we moeten dus eenmaal niet-seizoenaal differentiëren. Hier kan je ook nog bij opnemen dat de reeks niet seizoensgebonden was.

Post a new message

Dataset

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'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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26993&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=26993&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26993&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'Gwilym Jenkins' @ 72.249.127.135






Variance Reduction Matrix
V(Y[t],d=0,D=0)63.6715671342685Range31Trim Var.48.9787851240514
V(Y[t],d=1,D=0)1.00084506362122Range2Trim Var.NA
V(Y[t],d=2,D=0)2.09255533199195Range4Trim Var.0
V(Y[t],d=3,D=0)6.34675796715779Range8Trim Var.2.77320670289028
V(Y[t],d=0,D=1)8.27434611371057Range16Trim Var.3.65252525252525
V(Y[t],d=1,D=1)1.86001470327275Range4Trim Var.0
V(Y[t],d=2,D=1)3.85979381443299Range8Trim Var.2.27471133517645
V(Y[t],d=3,D=1)11.6280821334242Range16Trim Var.6.74884576582992
V(Y[t],d=0,D=2)16.9644405130473Range22Trim Var.8.4883687888299
V(Y[t],d=1,D=2)5.60330446369087Range8Trim Var.2.41988314715587
V(Y[t],d=2,D=2)11.4418426240622Range16Trim Var.6.11960099750623
V(Y[t],d=3,D=2)34.2796431002974Range28Trim Var.21.8737628999271

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 63.6715671342685 & Range & 31 & Trim Var. & 48.9787851240514 \tabularnewline
V(Y[t],d=1,D=0) & 1.00084506362122 & Range & 2 & Trim Var. & NA \tabularnewline
V(Y[t],d=2,D=0) & 2.09255533199195 & Range & 4 & Trim Var. & 0 \tabularnewline
V(Y[t],d=3,D=0) & 6.34675796715779 & Range & 8 & Trim Var. & 2.77320670289028 \tabularnewline
V(Y[t],d=0,D=1) & 8.27434611371057 & Range & 16 & Trim Var. & 3.65252525252525 \tabularnewline
V(Y[t],d=1,D=1) & 1.86001470327275 & Range & 4 & Trim Var. & 0 \tabularnewline
V(Y[t],d=2,D=1) & 3.85979381443299 & Range & 8 & Trim Var. & 2.27471133517645 \tabularnewline
V(Y[t],d=3,D=1) & 11.6280821334242 & Range & 16 & Trim Var. & 6.74884576582992 \tabularnewline
V(Y[t],d=0,D=2) & 16.9644405130473 & Range & 22 & Trim Var. & 8.4883687888299 \tabularnewline
V(Y[t],d=1,D=2) & 5.60330446369087 & Range & 8 & Trim Var. & 2.41988314715587 \tabularnewline
V(Y[t],d=2,D=2) & 11.4418426240622 & Range & 16 & Trim Var. & 6.11960099750623 \tabularnewline
V(Y[t],d=3,D=2) & 34.2796431002974 & Range & 28 & Trim Var. & 21.8737628999271 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26993&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]63.6715671342685[/C][C]Range[/C][C]31[/C][C]Trim Var.[/C][C]48.9787851240514[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]1.00084506362122[/C][C]Range[/C][C]2[/C][C]Trim Var.[/C][C]NA[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]2.09255533199195[/C][C]Range[/C][C]4[/C][C]Trim Var.[/C][C]0[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]6.34675796715779[/C][C]Range[/C][C]8[/C][C]Trim Var.[/C][C]2.77320670289028[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]8.27434611371057[/C][C]Range[/C][C]16[/C][C]Trim Var.[/C][C]3.65252525252525[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]1.86001470327275[/C][C]Range[/C][C]4[/C][C]Trim Var.[/C][C]0[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]3.85979381443299[/C][C]Range[/C][C]8[/C][C]Trim Var.[/C][C]2.27471133517645[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]11.6280821334242[/C][C]Range[/C][C]16[/C][C]Trim Var.[/C][C]6.74884576582992[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]16.9644405130473[/C][C]Range[/C][C]22[/C][C]Trim Var.[/C][C]8.4883687888299[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]5.60330446369087[/C][C]Range[/C][C]8[/C][C]Trim Var.[/C][C]2.41988314715587[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]11.4418426240622[/C][C]Range[/C][C]16[/C][C]Trim Var.[/C][C]6.11960099750623[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]34.2796431002974[/C][C]Range[/C][C]28[/C][C]Trim Var.[/C][C]21.8737628999271[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=26993&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26993&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)63.6715671342685Range31Trim Var.48.9787851240514
V(Y[t],d=1,D=0)1.00084506362122Range2Trim Var.NA
V(Y[t],d=2,D=0)2.09255533199195Range4Trim Var.0
V(Y[t],d=3,D=0)6.34675796715779Range8Trim Var.2.77320670289028
V(Y[t],d=0,D=1)8.27434611371057Range16Trim Var.3.65252525252525
V(Y[t],d=1,D=1)1.86001470327275Range4Trim Var.0
V(Y[t],d=2,D=1)3.85979381443299Range8Trim Var.2.27471133517645
V(Y[t],d=3,D=1)11.6280821334242Range16Trim Var.6.74884576582992
V(Y[t],d=0,D=2)16.9644405130473Range22Trim Var.8.4883687888299
V(Y[t],d=1,D=2)5.60330446369087Range8Trim Var.2.41988314715587
V(Y[t],d=2,D=2)11.4418426240622Range16Trim Var.6.11960099750623
V(Y[t],d=3,D=2)34.2796431002974Range28Trim Var.21.8737628999271


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 500 ; par2 = 0.5 ;
Parameters (R input):
par1 = 500 ; par2 = 0.5 ;
R code (references can be found in the software module):
n <- as.numeric(par1)
p <- as.numeric(par2)
heads=rbinom(n-1,1,p)
a=2*(heads)-1
b=diffinv(a,xi=0)
c=1:n
pheads=(diffinv(heads,xi=.5))/c
bitmap(file='test1.png')
op=par(mfrow=c(2,1))
plot(c,b,type='n',main='Law of Averages',xlab='Toss Number',ylab='Excess of Heads',lwd=2,cex.lab=1.5,cex.main=2)
lines(c,b,col='red')
lines(c,rep(0,n),col='black')
plot(c,pheads,type='n',xlab='Toss Number',ylab='Proportion of Heads',lwd=2,cex.lab=1.5)
lines(c,pheads,col='blue')
lines(c,rep(.5,n),col='black')
par(op)
dev.off()
b
par1 <- as.numeric(12)
x <- as.array(b)
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')