Approximating distributions of random functionals of Ferguson-Dirichlet priors
نویسنده
چکیده
The aim of this paper is to explore the possibility of approximating the Ferguson-Dirichlet prior and the distributions of its random functionals through the simulation of random probability measures. The proposed procedure is based on the constructive deenition illustrated in Sethuraman (1994) in conjunction with the use of a random stopping rule. This allows to set in advance the closeness to the distributions of interest. The distribution of the stopping rule is derived and the practicability of the simulating procedure is discussed. Suucient conditions for convergence of random functionals are provided. The numerical applications provided just sketch the idea of the variety of nonparametric procedures that can be easily and safely implemented in a proper Bayesian setting.
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تاریخ انتشار 1998