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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 computationTue, 02 Dec 2008 12:56:44 -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/02/t12282481568oi9c4av5osnhmw.htm/, Retrieved Sun, 19 May 2024 11:30:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28311, Retrieved Sun, 19 May 2024 11:30:33 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact146

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] [2008-12-02 19:56:44] [c4248bbb85fa4e400deddbf50234dcae] [Current]
Feedback Forum
2008-12-07 13:46:07 [Katrijn Truyman] [reply] 
Bij de spectraal analyse (of spectrum) wordt de tijdreeks ontbonden in regelmatige golfbewegingen. Een lage frequentie duidt op lange periodes of een LT-trend, deze periodes zijn dominant.
In het cummulatief periodogram zien we een steile stijging, hiermee kan 80% van de waarden verklaard worden.
2008-12-08 10:45:09 [Jessica Alves Pires] [reply] 
Hetgene dat de student zegt, is correct. We had de student er meer uitleg bij kunnen geven, bijvoorbeeld wat de frequenties eigenlijk betekenen. Het Cumulative Periodogram relateert de cumulatieve intensiteit van de cyclische golven die in de tijdreeks aanwezig zijn t.o.v. hun periode. Op de Y-as kan men de frequentie aflezen. Aan de linkerkant is de frequentie klein, dit geeft de lange termijn weer. De rechterkant stelt de korte termijn voor.

Ook had de student nog de Raw Periodogram mogen bespreken. Op de Raw Periodogram kan men zien dat er sprake is van een langzaam dalend patroon, er is dus sprake van een lange termijn trend. We moeten een niet seizoenale differentiatie opstellen om deze te verwijderen.
  2008-12-08 10:46:36 [Jessica Alves Pires] [reply] 
Typfout: Het eerste woordje van de tweede zin van de tweede alinea moet 'wel' zijn en dus niet 'we'.

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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=28311&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=28311&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28311&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


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 500 ; par2 = 0.5 ;
Parameters (R input):
par1 = 500 ; par2 = 0.5 ; par3 = ; par4 = ; par5 = ; par6 = ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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()