Markov-Switching Model Selection Using Kullback-Leibler Divergence
نویسندگان
چکیده
منابع مشابه
Markov-switching model selection using Kullback–Leibler divergence
In Markov-switching regression models, we use Kullback–Leibler (KL) divergence between the true and candidate models to select the number of states and variables simultaneously. Specifically, we derive a new information criterion, Markov switching criterion (MSC), which is an estimate of KL divergence. MSC imposes an appropriate penalty to mitigate the overretention of states in the Markov chai...
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ژورنال
عنوان ژورنال: SSRN Electronic Journal
سال: 2005
ISSN: 1556-5068
DOI: 10.2139/ssrn.711404