On information criteria and the generalized likelihood ratio test of model order selection
2004 (English)In: IEEE Signal Processing Letters, Vol. 11, no 10, 794-797 p.Article in journal (Refereed) Published
The Information Criterion (IC) rule and the Generalized Likelihood
Ratio Test (GLRT) have been usually considered to be two rather different
approaches to model order selection. However, we show here that a natural
implementation of the GLRT is in fact equivalent to the IC rule. A consequence
of this equivalence is that a specific IC rule, such as AIC or BIC, can be
viewed as a more direct way of implementing a GLRT with a specific
threshold. Another consequence of the equivalence, which is emphasized
herein, is a possibly original way of exploiting the information provided
by the local behavior of an IC for selecting the structure of
sparse models (the parameter vectors of which comprise ``many''
elements equal to zero).
Place, publisher, year, edition, pages
2004. Vol. 11, no 10, 794-797 p.
IdentifiersURN: urn:nbn:se:uu:diva-70176OAI: oai:DiVA.org:uu-70176DiVA: diva2:98087