R Functions for Time Series Analysis

Helpful sites for those who wish to use R for time series analysis.

Reference Card - R Functions for Time Series Analysis by Ricci

• http://cran.r-project.org/doc/contrib/Ricci-refcard-ts.pdf

CRAN Taskview for Time Series Analysis

• http://lib.stat.cmu.edu/R/CRAN/web/views/TimeSeries.html

• Also see CRAN Taskviews for Econometrics and Finance

Quick-R Time Series

• http://www.statmethods.net/advstats/timeseries.html

Using R for Time Series Analysis (Avril Coghlan)

• http://a-little-book-of-r-for-time-series.readthedocs.org/en/latest/src/timeseries.html#arima-models

Free (EZ) version of the book "Time Series Analysis and Its Applications: With R Examples (Third Edition)" by Robert Shumway and David Stoffer. (Link to info on 2nd Edition)

• http://www.stat.pitt.edu/stoffer/tsa3/tsa3EZ.pdf

• A quick tutorial - "an R time series quick fix" at http://www.stat.pitt.edu/stoffer/tsa3/R_toot.htm

All software has assumptions behind the algorithms of which the user should be aware. Here are links to a few issues for R.

• http://www.stat.pitt.edu/stoffer/tsa2/Rissues.htm

Time Series Analysis Teaching Page by James E. Monogan III

MORE RESOURCES

More R-related resources for time series.

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Probably the most useful. It seems to duplicate some of the Cowpertwait text but still looks like it might be very helpful (and the materials seem to be free?).

• Book Forecasting time series using R (http://robjhyndman.com/hyndsight/revolutionr2013/)

• [Link to] a one-hour talk by one of the authors on Forecasting time series using R.

• The URL of the book mentioned at the end has changed to http://www.otexts.org/fpp

• See (*) below for more detail.

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I just found this tutorial on ARIMA, which we might explore.

Tutorial for Box Jenkins (ARIMA) modeling (TSTutorial)

http://cran.cnr.berkeley.edu/web/packages/TSTutorial/vignettes/Stationary.pdf

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We won't get into this much in this course, but structural time series can be interesting and useful.

Structural Time Series (stsm)

http://cran.r-project.org/web/packages/stsm/index.html

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(*) more detail on Hyndman book

It seems that the materials (book, presentation, fpp R package, etc. online) are free.

(http://robjhyndman.com/hyndsight/fpp/)

From the author:

The book has it’s own R pack­age: fpp. This con­tains all the data sets used in the book, and also loads a few other pack­ages that are nec­es­sary to com­plete the examples.

The book is dif­fer­ent from other fore­cast­ing text­books in sev­eral ways.

• It is free and online, mak­ing it acces­si­ble to a wide audience.

• It is based around the fore­cast pack­age for R.

• It is con­tin­u­ously updated. You don’t have to wait until the next edi­tion for errors to be removed or new meth­ods to be dis­cussed. We will update the book frequently.

• There are dozens of real data exam­ples taken from our own con­sult­ing prac­tice. We have worked with hun­dreds of busi­nesses and orga­ni­za­tions help­ing them with fore­cast­ing issues, and this expe­ri­ence has con­tributed directly to many of the exam­ples given here, as well as guid­ing our gen­eral phi­los­o­phy of forecasting.

• We empha­size graph­i­cal meth­ods more than most fore­cast­ers. We use graphs to explore the data, analyze the valid­ity of the mod­els fit­ted and present the fore­cast­ing results.

Website with Shiny application for exploring ARIMA Transfer Function models.

• http://www.stat.cmu.edu:3838/hseltman/TransferFunctions/