Good introductions to time series (with R)

I am currently collecting data for an experiment into psychosocial characteristics associated with the experience of pain. As part of this, I am collecting GSR and BP measurements electronically from my participants, along with various self-report and implicit measures. I have a psychological background and am comfortable with factor analysis, linear models and experimental analysis.

My question is what are good (preferably free) resources available for learning about time series analysis. I am a total newb when it comes to this area, so any help would be greatly appreciated. I have some pilot data to practice on, but would like to have my analysis plan worked out in detail before I finish collected data.

If the provided references were also R related, that would be wonderful.

Edited: to change grammar and to add ‘self report and implicit measures’

Answer

This is a very large subject and there are many good books that cover it. These are both good, but Cryer is my favorite of the two:

  1. Cryer. “Time Series Analysis: With Applications in R” is a classic on the subject, updated to include R code.
  2. Shumway and Stoffer. “Time Series Analysis and Its Applications: With R Examples“.

A good free resource is Zoonekynd’s ebook, especially the time series section.

My first suggestion for seeing the R packages would be the free ebook “A Discussion of Time Series Objects for R in Finance” from Rmetrics. It gives lots of examples comparing the different time series packages and discusses some of the considerations, but it doesn’t provide any theory.

Eric Zivot’s “Modeling financial time series with S-PLUS” and Ruey Tsay’s “Analysis of Financial Time Series” (available in the TSA package on CRAN) are directed and financial time series but both provide good general references. I strongly recommend looking at Ruey Tsay’s homepage because it covers all these topics, and provides the necessary R code. In particular, look at the “Analysis of Financial Time Series”, and “Multivariate Time Series Analysis” courses.

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Shane

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