The nonparametric part of a semiparametric regression model usually involves prior specification for an infinite-dimensional parameter F. This paper introduces a class of finite mixture models based on B-spline distributions as an approximation to priors on the set of cumulative distribution...

A crucial problem in Bayesian posterior computation is efficient sampling from a univariate distribution, e.g. a full conditional distribution in applications of the Gibbs sampler. This full conditional distribution is usually non-conjugate, algebraically complex and computationally expensive...