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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 computationFri, 28 Nov 2008 06:06:23 -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/Nov/28/t1227877628ah6bm6t41r1ob47.htm/, Retrieved Mon, 20 May 2024 08:41:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=26069, Retrieved Mon, 20 May 2024 08:41:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact167

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 18:40:39] [b98453cac15ba1066b407e146608df68]
F         [Law of Averages] [Q4 - random walk] [2008-11-28 13:06:23] [55ca0ca4a201c9689dcf5fae352c92eb] [Current]
- RM D      [Spectral Analysis] [Spectrum] [2008-11-28 13:44:05] [e5d91604aae608e98a8ea24759233f66]
Feedback Forum
2008-12-06 16:39:54 [Kevin Engels] [reply] 
We kunnen uit deze plot afleiden dat er sprake is van een trend op lange termijn. Dit kan je zien door de stijle stijing in het begin van het cumulatieve periodogram en door de daling op lange termijn van het raw periodogram. Deze trend verklaart ongeveer 80% van de tijdreeks. Er is echter ook sprake van een seizoenale trend. Deze kan je herkennen door de getrapte figuur in het cumulatieve periodogram die verschijnt vanaf 0,8.
2008-12-07 12:40:27 [Kevin Neelen] [reply] 
Het verloop van het cumulatief periodogram kent een snelle initiële stijging wat wijst op een lange termijntrend. Deze trend verklaart ongeveer 75% van de tijdreeks. Er is niet echt een trapsgewijs verloop op te merken, wat duidt op de afwezigheid van seizoensinvloeden. Gezond verstand bevestigt deze veronderstelling, want er zijn in principe geen factoren die gaan bepalen of het nu kop of munt wordt.

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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'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=26069&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=26069&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26069&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 time1 seconds
R Server'George Udny Yule' @ 72.249.76.132


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
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()