Random Bernstein Polynomials
Sonia Petrone
Scandinavian Journal of Statistics, 1999, vol. 26, issue 3, 373-393
Abstract:
Random Bernstein polynomials which are also probability distribution functions on the closed unit interval are studied. The probability law of a Bernstein polynomial so defined provides a novel prior on the space of distribution functions on [0, 1] which has full support and can easily select absolutely continuous distribution functions with a continuous and smooth derivative. In particular, the Bernstein polynomial which approximates a Dirichlet process is studied. This may be of interest in Bayesian non‐parametric inference. In the second part of the paper, we study the posterior from a “Bernstein–Dirichlet” prior and suggest a hybrid Monte Carlo approximation of it. The proposed algorithm has some aspects of novelty since the problem under examination has a “changing dimension” parameter space.
Date: 1999
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Persistent link: https://EconPapers.repec.org/RePEc:bla:scjsta:v:26:y:1999:i:3:p:373-393
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