作者：VOVK, VG
摘要：A simple example shows that the classical theory of probability implies more than one can deduce via Kolmogorov's calculus of probability. Developing Dawid's ideas I propose a new calculus of probability which is free from this drawback. This calculus naturally leads to a new interpretation of probability. I argue that attempts to create a general empirical theory of probability should be abandoned and we should content ourselves with the logic of probability establishing relations between pro...
作者：HILL, BM
作者单位：University of Michigan System; University of Michigan
摘要：A class of parametric models, called splitting processes, is defined, by using de Finetti's concept of adherent mass. Such splitting processes give rise to complex mixtures of distributions. It is proved that the nonparametric Bayesian predictive procedure A(n), of Hill, holds exactly for a member of this class called a nested splitting process. The connection between A(n) and the Dirichlet process is stated and proved. A multivariate version of A(n), based on splitting processes, is proposed.
作者：WEST, M
摘要：Kernel density estimation techniques are used to smooth simulated samples from importance sampling function approximations to posterior distributions, resulting in revised approximations that are mixtures of standard parametric forms, usually multivariate normal or T-distributions. Adaptive refinement of such mixture approximations involves repeating this process to home-in successively on the posterior. In fairly low dimensional problems, this provides a general and automatic method of approx...
