Error exponents for composite hypothesis testing of Markov forest distributions

IEEE International Symposium on Information Theory - Proceedings

Volumn , Issue , 2010, Pages 1613-1617

  Tan, Vincent Y F ^a   Anandkumar, Animashree ^a   Willsky, Alan S ^a  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

Least favorable distribution; Markov forests; Neyman Pearson formulation; Worst case error exponent

Indexed keywords

BINARY HYPOTHESIS TESTING; CLOSED FORM; COMPOSITE HYPOTHESIS TESTING; EDGE WEIGHTS; ERROR EXPONENT; FOREST DISTRIBUTION; LEAST FAVORABLE DISTRIBUTION; MARKOV FORESTS; MUTUAL INFORMATIONS; NEYMAN-PEARSON; NULL HYPOTHESIS; SPANNING TREE; SUFFICIENT CONDITIONS; WORST-CASE ERRORS;

FRUITS; INFORMATION THEORY; STATISTICAL TESTS;

ERROR CORRECTION;

EID: 77955701505     PISSN: 21578103     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISIT.2010.5513399     Document Type: Conference Paper

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