As motivated by the recent change of the default model selection statistic in the R's forecast package from AIC to AICc, I am curious whether the latter is indeed applicable wherever the former is. I have a series of questions with this respect and here is the first one.
I know that to replace AIC with AICc everywhere is what the well-known book in (1) by Burnham and Anderson (non-statisticians), as summarized here, recommends. The book is sometimes uncritically referred to by younger statisticians, see e.g. comments to this blog post by Rob Hyndman, but the statistician Brian Ripley advised in a radically different way:
“Burnham and Anderson (2002) is a book I would recommend people NOT read until they have read the primary literature. I see no evidence that the authors have actually read Akaike’s papers." [quoted from [AIC MYTHS AND MISUNDERSTANDINGS] by Burnham-Anderson]
It does follow from what Ripley writes on the AIC and related theory that the warning should be taken seriously. I have both a good collection of Akaike's own papers and the Burnham-Anderson book. I will eventually have my own opinion on the quality of the book, but it will also help to know what the community of statisticians, both young and old, think on that. In particular, are there professors of statistics (or other good students of statistics) who explicitly recommended the book as a useful summary of knowledge on using AIC for model selection?
(1) Burnham, K. P. & Anderson, D. R. Model selection and multimodel inference: a practical information-theoretic approach Springer, 2002
PS. In reply to the recent "answer" stating that "Dr.Burnham is a Ph.D. statistician" I'd like to add this clarification. Yes, by himself he is a statistician, a Fellow of the ASA and the recipient of numerous professional awards, including Distinguished Achievement Medal from the ASA. But who says he is not? All I have said above is that as a pair of authors they are not statisticians and the book reflects this fact.