#### Title

Bayesian Inference For The Beta-Binomial Distribution Via Polynomial Expansions

#### Document Type

Article

#### Publication Date

3-1-2002

#### Published In

Journal Of Computational And Graphical Statistics

#### Abstract

A commonly used paradigm in modeling count data is to assume that individual counts are generated from a Binomial distribution, with probabilities varying between individuals according to a Beta distribution. The marginal distribution of the counts is then Beta-Binomial. Bradlow, Hardie, and Fader (2002, p. 189) make use of polynomial expansions to simplify Bayesian computations with Negative-Binomial distributed data. This article exploits similar expansions to facilitate Bayesian inference with data from the Beta-Binomial model. This has great application and computational importance to many problems, as previous research has resorted to computationally intensive numerical integration or Markov chain Monte Carlo techniques.

#### Recommended Citation

Philip J. Everson and E. T. Bradlow.
(2002).
"Bayesian Inference For The Beta-Binomial Distribution Via Polynomial Expansions".
*Journal Of Computational And Graphical Statistics*.
Volume 11,
Issue 1.
202-207.

http://works.swarthmore.edu/fac-math-stat/10