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Commentaires client les plus utiles sur Amazon.com (beta)
Amazon.com:4.2 étoiles sur 5 13 commentaires
17 internautes sur 17 ont trouvé ce commentaire utile
5.0 étoiles sur 5A great book on R!16 novembre 2009
Par Pd Farleigh - Publié sur Amazon.com
Format:Broché|Achat authentifié par Amazon
This is a cracking book on applying R to time series analysis. The best parts of the book are all of the worked examples, the accompanying data sets and several different ways to calculate seasonality.
The book is better than most on time series, because it does not neglect the de-trending process needed to get stationery residuals. If you use just the lm() command in R to do this before, then the real gem in this book is the advice to use the gls() command from the nlme library instead (to get the confidence intervals right).
Overall, a very good book that is applied to R but has enough mathematical backing for the techniques presented. However, this is a book about applying time series analysis in R. If you seek a more algebraic treatment, then this is not the book I'm afraid, but it would be a great supplement!
9 internautes sur 9 ont trouvé ce commentaire utile
5.0 étoiles sur 5Nice book26 janvier 2010
Par Dimitri Shvorob - Publié sur Amazon.com
Format:Broché
Full marks on coverage and "technical vs. accessible" trade-off; a concise, rigorous and user-friendly introduction to time series analysis in R, helpful for both statisics and R beginners, and an appealing complementary textbook in a graduate course.
7 internautes sur 7 ont trouvé ce commentaire utile
5.0 étoiles sur 5QUite good introduction22 mars 2010
Par AGJr - Publié sur Amazon.com
Format:Broché|Achat authentifié par Amazon
Differently from many other books in the "Use R!" series, this one is very didatic and comprehensive. It covers all important functions and applications in time series analysis, ad it's good for both the graduate and undergraduate students or the casual researcher.