Bayesian Estimation of Unimodal Distributions
Nov 30 1993
In this paper, we estimate unimodal distribution functions (DFs) from a Bayesian perspective. A DF is assumed to be ogive, that is to say one that switches from convex to concave with an unknown change-point. Monte Carlo methods are described which provide a full Bayesian solution for the modelling of unimodal DFs.
Keywords:Unimodal distributions, switch-point, convex, concave, gibbs sampling