artículo
Some issues in nonparametric Bayesian modelling using species sampling models
Fecha
2008Registro en:
10.1177/1471082X0700800102
1471-082X
WOS:000257402200002
Autor
Navarrete, Carlos
Quintana, Fernando A.
Mueller, Peter
Institución
Resumen
We review some aspects of nonparametric Bayesian data analysis with discrete random probability measures. We focus on the class of species sampling models (SSMs). We critically investigate the common use of the Dirichlet process (DP) prior as a default SSM choice. We discuss alternative prior specifications from a theoretical, computational and data analysis perspective. We conclude with a recommendation to consider SSM priors beyond the special case of the DP prior, and make specific recommendations on how different choices can be used to reflect prior information and how they impact the desired inference. We show the required changes in the posterior simulation schemes, and argue that the additional generality can be achieved without additional computational effort.