Bayesian Inference, Entropy, and the Multinomial Distribution Export

@misc{citeulike:1606606, abstract = {Instead of maximum-likelihood or MAP, Bayesian inference encourages the use of predictive densities and evidence scores. This is illustrated in the context of the multinomial distribution, where predictive estimates are often used but rarely described as Bayesian. By using an entropy approximation to the evidence, many Bayesian quantities can be expressed in information-theoretic terms. For example, testing whether two samples come from the same distribution or testing whether two variables are ...}, author = {Minka, Thomas P.}, citeulike-article-id = {1606606}, citeulike-linkout-0 = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.48.7162}, keywords = {bayesian, entropy, multinomial}, posted-at = {2007-08-30 05:34:36}, priority = {2}, title = {Bayesian Inference, Entropy, and the Multinomial Distribution}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.48.7162} }

TY - GEN ID - citeulike:1606606 L3 - citeulike-article-id:1606606 N2 - Instead of maximum-likelihood or MAP, Bayesian inference encourages the use of predictive densities and evidence scores. This is illustrated in the context of the multinomial distribution, where predictive estimates are often used but rarely described as Bayesian. By using an entropy approximation to the evidence, many Bayesian quantities can be expressed in information-theoretic terms. For example, testing whether two samples come from the same distribution or testing whether two variables are ... TI - Bayesian Inference, Entropy, and the Multinomial Distribution KW - bayesian KW - entropy KW - multinomial AU - Minka, Thomas UR - http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.48.7162 ER -