A Bayesian nonparametric method for prediction in EST analysis. - Antonio Lijoi; Ramsés H. Mena; Igor Prünster (BMC Bioinform., 2007)

A Bayesian Nonparametric Approach for Comparing Clustering Structures in EST Libraries. - Antonio Lijoi; Ramsés H. Mena; Igor Prünster (J. Comput. Biol., 2008)

Vectors of two-parameter Poisson-Dirichlet processes. - Fabrizio Leisen; Antonio Lijoi (J. Multivar. Anal., 2011)

Dependent mixture models: Clustering and borrowing information. - Antonio Lijoi; Bernardo Nipoti; Igor Prünster (Comput. Stat. Data Anal., 2014)

Discussion of "On simulation and properties of the stable law" by L. Devroye and L. James. - Antonio Lijoi; Igor Prünster (Stat. Methods Appl., 2014)

Are Gibbs-Type Priors the Most Natural Generalization of the Dirichlet Process? - Pierpaolo De Blasi; Stefano Favaro; Antonio Lijoi; Ramsés H. Mena; Igor Prünster; Matteo Ruggiero (IEEE Trans. Pattern Anal. Mach. Intell., 2015)

Full Bayesian inference with hazard mixture models. - Julyan Arbel; Antonio Lijoi; Bernardo Nipoti (Comput. Stat. Data Anal., 2016)

Introduction to the special issue on Bayesian Nonparametrics. - Alessio Benavoli; Antonio Lijoi; Antonietta Mira (Int. J. Approx. Reason., 2017)

Bayesian prediction with multiple-samples information. - Federico Camerlenghi; Antonio Lijoi; Igor Prünster (J. Multivar. Anal., 2017)

Prior Sensitivity Analysis in a Semi-Parametric Integer-Valued Time Series Model. - Helton Graziadei; Antonio Lijoi; Hedibert Freitas Lopes; Paulo C. Marques F.; Igor Prünster (Entropy, 2020)

Sampling hierarchies of discrete random structures. - Antonio Lijoi; Igor Prünster; Tommaso Rigon (Stat. Comput., 2020)

Posterior Asymptotics for Boosted Hierarchical Dirichlet Process Mixtures. - Marta Catalano; Pierpaolo De Blasi; Antonio Lijoi; Igor Prünster (J. Mach. Learn. Res., 2022)