We present a new model selection criterion that can be easily approximated by a Monte Carlo sampling algorithm. It is shown that under certain conditions the new criterion is related to both the deviance and the Akaike information criteria. The new criterion can be easily extended to an arbitrary non-negative objective function using the extended Baum-Welch procedure.
By: Avishy Carmi; Dimitri Kanevsky
Published in: RC24670 in 2008
LIMITED DISTRIBUTION NOTICE:
This Research Report is available. This report has been submitted for publication outside of IBM and will probably be copyrighted if accepted for publication. It has been issued as a Research Report for early dissemination of its contents. In view of the transfer of copyright to the outside publisher, its distribution outside of IBM prior to publication should be limited to peer communications and specific requests. After outside publication, requests should be filled only by reprints or legally obtained copies of the article (e.g., payment of royalties). I have read and understand this notice and am a member of the scientific community outside or inside of IBM seeking a single copy only.
Questions about this service can be mailed to reports@us.ibm.com .