Error exponents for composite hypothesis testing of Markov forest distributions

The problem of composite binary hypothesis testing of Markov forest (or tree) distributions is considered. The worst-case type-II error exponent is derived under the Neyman-Pearson formulation. Under simple null hypothesis, the error exponent is derived in closed-form and is characterized in terms o...

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Bibliographic Details
Main Authors: Tan, Vincent Yan Fu, Anandkumar, Animashree, Willsky, Alan S.
Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Format: Article
Language:en_US
Published: Institute of Electrical and Electronics Engineers (IEEE) 2012
Online Access:http://hdl.handle.net/1721.1/73578
https://orcid.org/0000-0003-0149-5888

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