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June 27, 2013


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I have been investigating the bibliography for time series analysis for a long time now, and though I have already found majority of those books it's nice to have a repository of links like this article.

Thank you Joseph.

Thanks for the article. The word "oversimplifying" is misspelled.

@Bostonian clearly the word "oversimplifying" has not yet been oversimplified.

Thank you all for the kind words and the spelling help.
I appreciate it.

For a very pragmatic approach and one of the best introductory text I've seen consider
Forecasting: principles and practice
An online textbook by Rob J Hyndman and George Athanasopoulos

Thank you for the very nice summary of where one should start these days with learning time series analysis with R.

Just in case someone is trying to run the code under OS X,
The command:

fit <- auto.arima(IBM.1982)

doesn't work unless you change it to:

fit <- auto.arima(as.ts(IBM.1982))

The book you refer to as Cowpertwait's has a second author, Andrew Metcalfe.

Minor typo: "AIRMA" -> "ARIMA" at the end of paragraph 4.

I think you forgot "Analysis of Financial Time Series" by Ruey S. Tsay, Wiley-Interscience 2010, Probability and Statistics

I would also add to the list the excellent Wavelet Methods in Statistics with R by G.P. Nason (Springer 2008)

One comment about the RMetrics ebooks: I find them dramatically expensive. Also, I have had a lot of problems with the RMetrics packages like fPortfolio, which seems to be only semi-functional, at best. I would have been very upset to pay those prices for the RMetrics documentation only to find that the software didn't work.

Bernand Pfaff's 'Analysis of Integrated and Cointegrated Time Series with R' is missing from your list. This author is one of the leading contributer's to the gratis software we call R.

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