Error exponents for composite hypothesis testing of Markov forest distributions

dc.contributor.author	Tan, Vincent Yan Fu
dc.contributor.author	Anandkumar, Animashree
dc.contributor.author	Willsky, Alan S.
dc.date.accessioned	2012-10-03T19:16:37Z
dc.date.available	2012-10-03T19:16:37Z
dc.date.issued	2010-07
dc.date.submitted	2010-06
dc.identifier.isbn	978-1-4244-7891-0
dc.identifier.isbn	978-1-4244-7890-3
dc.identifier.uri	http://hdl.handle.net/1721.1/73578
dc.description.abstract	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 of the so-called bottleneck edge of the forest distribution. The least favorable distribution for detection is shown to be Markov on the second-best max-weight spanning tree with mutual information edge weights. A necessary and sufficient condition to have positive error exponent is derived.	en_US
dc.language.iso	en_US
dc.publisher	Institute of Electrical and Electronics Engineers (IEEE)	en_US
dc.relation.isversionof	http://dx.doi.org/10.1109/ISIT.2010.5513399	en_US
dc.rights	Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.	en_US
dc.source	IEEE	en_US
dc.title	Error exponents for composite hypothesis testing of Markov forest distributions	en_US
dc.type	Article	en_US
dc.identifier.citation	Tan, Vincent Y. F., Animashree Anandkumar, and Alan S. Willsky. “Error Exponents for Composite Hypothesis Testing of Markov Forest Distributions.” IEEE International Symposium on Information Theory Proceedings (ISIT), 2010. 1613–1617. © Copyright 2010 IEEE	en_US
dc.contributor.department	Massachusetts Institute of Technology. Laboratory for Information and Decision Systems	en_US
dc.contributor.department	Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science	en_US
dc.contributor.mitauthor	Tan, Vincent Yan Fu
dc.contributor.mitauthor	Anandkumar, Animashree
dc.contributor.mitauthor	Willsky, Alan S.
dc.relation.journal	Proceedings of the IEEE International Symposium on Information Theory Proceedings (ISIT), 2010	en_US
dc.identifier.mitlicense	PUBLISHER_POLICY	en_US
dc.eprint.version	Final published version	en_US
dc.type.uri	http://purl.org/eprint/type/ConferencePaper	en_US
dspace.orderedauthors	Tan, Vincent Y. F.; Anandkumar, Animashree; Willsky, Alan S.	en