Thanks, Tom, for the reply as well as to the reference to Claeskens & Hjort.
Ravi ________________________________________ From: Thomas Lumley [tlum...@uw.edu] Sent: Thursday, May 03, 2012 4:41 PM To: Mark Leeds Cc: Ravi Varadhan; r-devel@r-project.org Subject: Re: [Rd] The constant part of the log-likelihood in StructTS On Thu, May 3, 2012 at 3:36 AM, Mark Leeds <marklee...@gmail.com> wrote: > Hi Ravi: As far as I know ( well , really read ) and Bert et al can say > more , the AIC is not dependent on the models being nested as long as the > sample sizes used are the same when comparing. In some cases, say comparing > MA(2), AR(1), you have to be careful with sample size usage but there is no > nesting requirement for AIC atleast, I'm pretty sure. This is only partly true. The expected value of the AIC will behave correctly even if models are non-nested, but there is no general guarantee that the standard deviation is small, so AIC need not even asymptotically lead to optimal model choice for prediction in arbitrary non-nested models. Having said that, 'nearly' nested models like these are probably ok. I believe it's sufficient that all your models are nested in a common model, with a bound on the degree of freedom difference, but my copy of Claeskens & Hjort's book on model selection and model averaging is currently with a student so I can't be definitive. -thomas -- Thomas Lumley Professor of Biostatistics University of Auckland ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel