title: On species sampling sequences induced by residual allocation models.
abstract: We discuss fully Bayesian inference in a class of species sampling models that are induced by residual allocation (sometimes called stick-breaking) priors on almost surely discrete random measures. This class provides a generalization of the well-known Ewens sampling formula that allows for additional flexibility while retaining computational tractability. In particular, the procedure is used to derive the exchangeable predictive probability functions associated with the generalized Dirichlet process of Hjort (2000) and the probit stick-breaking prior of Chung and Dunson (2009) and Rodriguez and Dunson (2011). The procedure is illustrated with applications to genetics and nonparametric mixture modeling.
authors.affiliation: Department of Applied Mathematics and Statistics, University of California, Santa Cruz, USA.
authors.forename: Abel
authors.initials: A
authors.lastname: Rodríguez
authors.affiliation: Departamento de Estadística, Facultad de Matemáticas, Pontificia Universidad Católica de Chile, Santiago, Chile.
authors.forename: Fernando A
authors.initials: FA
authors.lastname: Quintana
keywords: Exchangeable partition probability function; Generalized Dirichlet process; Probit-stick breaking process; Size-biased permutation