Giovanni Azua wrote:
Hello Denis,
(1) I appreciate your feedback, however, I feel I have all the right to ask a specific question related R namely what's the interpretation of the acf function plot. I gave away the information that it is a homework because many times people before helping ask what's the context for the question at hand. If I don't understand something I will for sure ask. I don't have anything to hide so I don't care if there are professors subscribed to this list. My ultimate goal is to learn and it doesn't really matter whether it is studying a book, asking an assistant or asking in a forum.
(2) After looking in many references and not finding any clue ... I Googled for
information and found that I should be "looking for cyclic patterns" i.e.
oscillations? There are none in this dataset so I presume there would not be any
autocorrelation, oder?
(3) This is something very unfortunate ... the course Lectures are great, the
course script is very comprehensive, however, the assignments many times
include questions that are a bit off topic like in this case of Time Series and
includes no actual reference ... so it is no surprise that even after
diligently attending all lectures and doing all exercises I get stuck. Please
recommend what's the best book in this topic of Time Series analysis maybe with
R. I will buy it.
(4) Yes they mentioned something like this in the assignment "Dependency can be
verified by showing that under the model, Cov(X_t^2,X_{t-h}^2) \neq 0, h > 0
(complicated). Plot and interpret the autocorrelation functions of X_t and X_t^2 for the
BMW-dataset." http://stat.ethz.ch/teaching/lectures/FS_2010/CompStat/series4.pdf
Thank you.
Best regards,
Giovanni
There are at least three R-specific time series books, all of which
would deal with interpretation of an acf.
Shumway and Stoffer
Cowpertwait and Metcalfe
Cryer and Chan
See the books page: http://www.r-project.org/doc/bib/R-books.html
Shumway and Stoffer is probably the most advanced of these but in no way
difficult. There are a number of other more specialized and advanced
texts also. Off the top of my head, Pfaff, Hyndman, ...
David Scott
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Phone: +64 9 923 5055, or +64 9 373 7599 ext 85055
Email: d.sc...@auckland.ac.nz, Fax: +64 9 373 7018
Director of Consulting, Department of Statistics
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