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Combining Marginal Probability Distributions via Minimization of Weighted Sum of Kullback-Leibler Divergences
- 1.0359399 - ÚTIA 2012 RIV US eng J - Journal Article
Kracík, Jan
Combining Marginal Probability Distributions via Minimization of Weighted Sum of Kullback-Leibler Divergences.
International Journal of Approximate Reasoning. Roč. 52, č. 6 (2011), s. 659-671. ISSN 0888-613X. E-ISSN 1873-4731
R&D Projects: GA ČR GA102/08/0567
Institutional research plan: CEZ:AV0Z10750506
Keywords : combining probabilities * Kullback-Leibler divergence * maximum likelihood * expert opinions * linear opinion pool
Subject RIV: BB - Applied Statistics, Operational Research
Impact factor: 1.948, year: 2011
http://library.utia.cas.cz/separaty/2011/AS/kracik-0359399.pdf
The paper deals with the problem of combining marginal probability distributions as a means for aggregating pieces of expert information. The combined distribution is searched as a minimizer of a weighted sum of Kullback–Leibler divergences of the given marginal distributions and corresponding marginals of the searched one. Necessary and sufficient conditions for a distribution to be a minimizer are stated. For discrete random variables an iterative algorithm for approximate solution of the minimization problem is proposed and its convergence is proved.
Permanent Link: http://hdl.handle.net/11104/0197196
Number of the records: 1