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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 12:46:26 -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/t1228160839fdgqaa1s7k036qc.htm/, Retrieved Sun, 05 May 2024 11:11:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=27264, Retrieved Sun, 05 May 2024 11:11:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact242
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 18:40:39] [b98453cac15ba1066b407e146608df68]
F       [Law of Averages] [] [2008-11-30 21:31:33] [8b0d202c3a0c4ea223fd8b8e731dacd8]
F           [Law of Averages] [q4] [2008-12-01 19:46:26] [2fdb1a8e4a6fa49ce74bdce2c154874d] [Current]
Feedback Forum
2008-12-08 10:19:22 [Joris Deboel] [reply
Raw periodogram:
men gaat de tijdreeks ontbinden in samengestelde golfbewegingen.
De frequentie lees je af op de x-as. Bij de raw periodogram ziet men dat de grafiek hoger is bij een lage frequentie dan bij een hoge frequentie. Dit betekent dat de tijdreeks traag evolueert. De tijdreeks bestaat het meest uit lange termijn golfbewegingen.

Cumulative periodogram: de intensiteit optellen.
Deze grafiek geeft aan hoeveel procent wordt verklaard door extreem trage golfbeweging. Je ziet dat de grafiek zich bevindt rond de 95 % op de x-as. Dus 95 % verklaart dat het lange termijn golfbewegingen zijn.
De grafiek bevindt zich bovendien buiten de stippenlijnen, het is hier dus significant. Als de grafiek tussen de stippenlijn zou liggen, zou er geen enkel patroon zijn.

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Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 5 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27264&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27264&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27264&T=0

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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 time5 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001



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
x <- b
bitmap(file='test1.png')
r <- spectrum(x,main='Raw Periodogram')
dev.off()
r
bitmap(file='test2.png')
cpgram(x,main='Cumulative Periodogram')
dev.off()