48 citations · 199 across the 12 of their papers we have counts for
6 papers · 1 filter
Multivariate Species Sampling Models
Beatrice Franzolini, Antonio Lijoi, Igor Prünster +1
Species sampling processes have long served as the fundamental framework for modeling random discrete distributions and exchangeable sequences. However, data arising from distinct…
A Bayesian nonparametric approach to modeling market share dynamics
Igor Prünster, Matteo Ruggiero
We propose a flexible stochastic framework for modeling the market share dynamics over time in a multiple markets setting, where firms interact within and between markets. Firms un…
Asymptotics for a Bayesian nonparametric estimator of species variety
Stefano Favaro, Antonio Lijoi, Igor Prünster
In Bayesian nonparametric inference, random discrete probability measures are commonly used as priors within hierarchical mixture models for density estimation and for inference on…
Asymptotics for posterior hazards
Pierpaolo De Blasi, Giovanni Peccati, Igor Prünster
An important issue in survival analysis is the investigation and the modeling of hazard rates. Within a Bayesian nonparametric framework, a natural and popular approach is to model…
On rates of convergence for posterior distributions in infinite-dimensional models
Stephen G. Walker, Antonio Lijoi, Igor Prünster
This paper introduces a new approach to the study of rates of convergence for posterior distributions. It is a natural extension of a recent approach to the study of Bayesian consi…
Normalized random measures driven by increasing additive processes
Luis E. Nieto-Barajas, Igor Prunster, Stephen G. Walker
This paper introduces and studies a new class of nonparametric prior distributions. Random probability distribution functions are constructed via normalization of random measures d…