Bayesian nonparametric estimators derived from conditional Gibbs structures (2008)
Lijoi, Antonio, Prünster, Igor, Walker, Stephen G.
We consider discrete nonparametric priors which induce Gibbs-type exchangeable random partitions and investigate their posterior behavior in detail. In particular, we deduce conditional distributions...
A Bayesian nonparametric method for prediction in EST analysis (2007)
Lijoi, Antonio, Mena, Ramsés H, Prünster, Igor
Abstract Background Expressed sequence tags (ESTs) analyses are a fundamental tool for gene identification in organisms. Given a preliminary EST sample from a certain library, several statistical...
On rates of convergence for posterior distributions in infinite-dimensional models (2007)
Walker, Stephen G., Lijoi, Antonio, Prünster, Igor
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 consistency. In...
Linear and quadratic functionals of random hazard rates: an asymptotic analysis (2006)
Peccati, Giovanni, Prünster, Igor
A popular Bayesian nonparametric approach to survival analysis consists in modeling hazard rates as kernel mixtures driven by a completely random measure. In this paper we derive asymptotic results...
Linear and quadratic functionals of random hazard rates: an asymptotic analysis (2006)
Peccati, Giovanni, Prünster, Igor
A popular Bayesian nonparametric approach to survival analysis consists in modeling hazard rates as kernel mixtures driven by a completely random measure. In this paper we derive asymptotic results...
Linear and quadratic functionals of random hazard rates: an asymptotic analysis (2006)
Peccati, Giovanni, Prünster, Igor
A popular Bayesian nonparametric approach to survival analysis consists in modeling hazard rates as kernel mixtures driven by a completely random measure. In this paper we derive asymptotic results...
Linear and quadratic functionals of random hazard rates: an asymptotic analysis (2006)
Peccati, Giovanni, Prünster, Igor
A popular Bayesian nonparametric approach to survival analysis consists in modeling hazard rates as kernel mixtures driven by a completely random measure. In this paper we derive asymptotic results...
Distributions of linear functionals of two parameter Poisson--Dirichlet random measures (2006)
James, Lancelot F., Lijoi, Antonio, Prünster, Igor
The present paper provides exact expressions for the probability distributions of linear functionals of the two-parameter Poisson--Dirichlet process $\operatorname {PD}(\alpha,\theta)$. We obtain...
Normalized random measures driven by increasing additive processes (2004)
Nieto-Barajas, Luis E., Prünster, Igor, Walker, Stephen G.
This paper introduces and studies a new class of nonparametric prior distributions. Random probability distribution functions are constructed via normalization of random measures driven by increasing...
Extending Doob's consistency theorem to nonparametric densities (2004)
Lijoi, Antonio, Prünster, Igor, Walker, Stephen G.
We extend Doob's well-known result on Bayesian consistency. The extension covers the case where the nonparametric prior is fully supported by densities. However, our use of martingales differs from...
Distributional results for means of normalized random measures with independent increments (2003)
Regazzini, Eugenio, Lijoi, Antonio, Prünster, Igor
We consider the problem of determining the distribution of means of random probability measures which are obtained by normalizing increasing additive processes. A solution is found by resorting to a...
Controlling the reinforcement in Bayesian non-parametric mixture models
Antonio Lijoi, Ramsés H. Mena, Igor Prünster
The paper deals with the problem of determining the number of components in a mixture model. We take a Bayesian non-parametric approach and adopt a hierarchical model with a suitable non-parametric...
Hierarchical mixture modelling with normalized inverse Gaussian priors.
Antonio Lijoi, Ramsés H. Mena, Igor Prünster
In recent years the Dirichlet process prior has experienced a great success in the context of Bayesian mixture modelling. The idea of overcoming discreteness of its realizations by exploiting it in...
On consistency of nonparametric normal mixtures for Bayesian density estimation.
Antonio Lijoi, Igor Prünster, Stephen G. Walker
The past decade has seen a remarkable development in the area of Bayesian nonparametric inference both from a theoretical and applied perspective. As for the latter, the celebrated Dirichlet process...
On rates of convergence for posterior distributions in infinite–dimensional models.
Antonio Lijoi, Igor Prünster, Stephen G. Walker
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 consistency. Crucially,...
Contributions to the understanding of Bayesian consistency.
Antonio Lijoi, Igor Prünster, Stephen G. Walker
Consistency of Bayesian nonparametric procedures has been the focus of a considerable amount of research. Here we deal with strong consistency for Bayesian density estimation. An awkward consequence...
Bayesian Nonparametric Estimation of the Probability of Discovering New Species
We consider the problem of evaluating the probability of discovering a certain number of new species in a new sample of population units, conditional on the number of species recorded in a basic...
Bayesian Nonparametric Analysis for a Generalized Dirichlet Process Prior
Antonio Lijoi, Ramsés Mena, Igor Prünster
Bayesian nonparametric inference, Dirichlet process, generalized gamma convolutions, Lauricella hypergeometric functions, means of random probability measures, predictive distributions, 62F15, 60G57,