Papers
Articles in peer-reviewed Journals
[1] Catalano, M., Lavenant, H., Lijoi, A., Prünster, I. (2024). A Wasserstein index of dependence for random measures. Journal of the American Statistical Association, forthcoming. (pdf)
[2] Ascolani, F., Franzolini, B., Lijoi, A., Prünster, I. (2024). Nonparametric priors with full-range borrowing of information. Biometrika, forthcoming. (pdf)
[3] Catalano, M., Del Sole, C., Lijoi, A., Prünster, I. (2024). A unified approach to hierarchical random measures. D. Basu Centennial Volume, Sankhya, forthcoming. (pdf)
[4] Lijoi, A., Prünster, I., Rigon, T. (2024). Finite-dimensional discrete random structures and Bayesian clustering. Journal of the American Statistical Association, 119, 929-941. (pdf)
[5] Catalano, M., Lijoi, A., Prünster, I., Rigon, T. (2023). Bayesian modeling via discrete nonparametric priors. Japanese Journal of Statistics and Data Science, 6, 607-624 (pdf)
[6] Franzolini, B., Lijoi, A., Prünster, I. (2023). Model Selection for Maternal Hypertensive Disorders with Symmetric Hierarchical Dirichlet Processes. The Annals of Applied Statistics, 17, 313-332. (pdf)
[7] Lijoi, A., Prünster, I., Rebaudo, G. (2023). Flexible clustering via hidden hierarchical Dirichlet priors. Scandinavian Journal of Statistics, 50, 213-234. (pdf)
[8] Canale, A., Lijoi, A., Nipoti, B., Prünster, I. (2023). Inner spike and slab Bayesian nonparametric models. Econometrics and Statistics, 27, 120-135. (pdf)
[9] Catalano, M., De Blasi, P., Lijoi, A., Prünster, I. (2022). Posterior asymptotics for boosted hierarchical Dirichlet process mixtures. Journal of Machine Learning Research, 23 (80), 1-23. (pdf)
[10] De Blasi, P., Mena, R.H., Prünster, I. (2022). Asymptotic behavior of the number of distinct values in a sample from the geometric stick-breaking process. Annals of the Institute of Statistical Mathematics, 74, 143-165. (pdf)
[11] Catalano, M., Lijoi, A., Prünster, I. (2021). Measuring dependence in the Wasserstein distance for Bayesian nonparametric models. The Annals of Statistics, 49, 2916-2947. (pdf)
[12] Arbel, J., Kon Kam King, G., Lijoi, A., Nieto-Barajas, L.E., Prünster, I (2021). BNPdensity: Bayesian nonparametric mixture modelling in R. Australian & New Zealand Journal of Statistics, 63, 542-564. (pdf)
[13] Camerlenghi, F., Lijoi, A., Prünster, I. (2021). Survival analysis via hierarchically dependent mixture hazards. The Annals of Statistics, 49, 863-884. (pdf)
[14] Lijoi, A., Prünster, I., Rigon, T. (2020). The Pitman-Yor multinomial model for mixture modelling. Biometrika, 107, 891-906. (pdf)
[15] Catalano, M., Lijoi, A., Prünster, I. (2020). Approximation of Bayesian models for time-to-event data. Electronic Journal of Statistics, 14, 3366-3395. (pdf)
[16] Lijoi, A., Prünster, I., Rigon, T. (2020). Sampling hierarchies of discrete random structures. Statistics and Computing, 30, 1591-1607. (pdf)
[17] De Blasi, P., Martinez, A.E., Mena, R.H., Prünster, I. (2020). On the inferential implications of decreasing weight structures in mixture models. Computational Statistics & Data Analysis, 147, 106940. (pdf)
[18] Graziadei, H., Lijoi, A., Lopes, H.F., Marques F., P.C, Prünster, I. (2020). Prior sensitivity analysis in a semi-parametric integer-valued time series model. Entropy, 22, 69. (pdf)
[19] Camerlenghi, F., Dunson, D.B., Lijoi, A., Prünster, I., Rodriguez, A. (2019). Latent nested nonparametric priors (with discussion). Bayesian Analysis, 15, 1303-1356. (pdf)
[20] Camerlenghi, F., Lijoi, A., Orbanz, P., Prünster, I. (2019). Distribution theory for hierarchical processes. The Annals of Statistics, 47, 67-92. (pdf)
[21] Arbel, J., De Blasi, P., Prünster, I. (2019). Stochastic approximations to the Pitman-Yor process. Bayesian Analysis, 15, 1201-1219. (pdf)
[22] Camerlenghi, F., Lijoi, A., Prünster, I. (2018). Bayesian nonparametric inference beyond the Gibbs-type framework. Scandinavian Journal of Statistics, 45, 1062-1091. (pdf)
[23] Anzarut, M., Mena, R.H., Nava, C., Prünster, I. (2018). Poisson driven stationary Markov models. Journal of Business & Economic Statistics, 36, 684-694. (pdf)
[24] Canale, A., Lijoi, A., Nipoti, B., Prünster, I. (2017). On the Pitman-Yor process with spike and slab base measure. Biometrika, 104, 681-697. (pdf)
[25] Camerlenghi, F., Lijoi, A., Prünster, I. (2017). Bayesian prediction with multiple-samples information. Journal of Multivariariate Analysis, 156, 18-28. (pdf)
[26] Canale, A., Prünster, I. (2017). Robustifying Bayesian nonparametric mixtures for count data. Biometrics, 73, 174-184. (pdf)
[27] Arbel, J., Prünster, I. (2017). A moment-matching Ferguson & Klass algortihm. Statistics and Computing, 27, 3-17. (pdf)
[28] Lijoi, A., Muliere, P., Prünster, I., Taddei, F. (2016). Innovation, growth and aggregate volatility from a Bayesian nonparametric perspective. Electronic Journal of Statistics, 10, 2179-2203. (pdf)
[29] Favaro, S., Lijoi, A., Nava, C., Nipoti, B., Prünster, I., Teh, Y.W. (2016). On the stick-breaking representation for homogeneous NRMIs. Bayesian Analysis, 11, 697-724. (pdf)
[30] De Blasi, P., Favaro, S., Lijoi, A., Mena, R., Prünster, I., Ruggiero, M. (2015). Are Gibbs-type priors the most natural generalization of the Dirichlet process? IEEE Transactions on Pattern Analysis and Machine Intelligence, 37, 212-229. (pdf)
[31] El-Dakkak, O., Peccati, G., Prünster, I. (2014). Exchangeable Hoeffding-decomposition over finite sets: a characterization and counterexamples. Journal of Multivariate Analysis, 131, 51-64. (pdf)
[32] Lijoi, A., Nipoti, B., Prünster, I. (2014). Bayesian inference with dependent normalized completely random measures. Bernoulli, 20, 1260-1291. (pdf)
[33] Lijoi, A., Nipoti, B., Prünster, I. (2014). Dependent mixture models: clustering and borrowing information. Computational Statistics & Data Analysis, 71, 417-433. (pdf)
[34] Barrios, E., Lijoi, A., Nieto-Barajas, L.E., Prünster, I. (2013). Modeling with normalized random measure mixture models. Statistical Science, 28, 313-334. (pdf)
[35] Favaro, S., Lijoi, A., Prünster, I. (2013). Conditional formulae for Gibbs-type exchangeable random partitions. The Annals of Applied Probability, 23, 1721-1754. (pdf)
[36] De Blasi, P., Lijoi, A., Prünster, I. (2013). An asymptotic analysis of a class of discrete nonparametric priors. Statistica Sinica, 23, 1299-1322. (pdf)
[37] Prünster, I., Ruggiero, M. (2013). A Bayesian nonparametric approach to modeling market share dynamics. Bernoulli, 19, 64-92. (pdf)
[38] Favaro, S., Lijoi, A., Prünster, I. (2012). A new estimator of the discovery probability. Biometrics, 68, 1188-1196. (pdf with a minor correction)
[39] Favaro, S., Lijoi, A., Prünster, I. (2012). On the stick-breaking representation of normalized inverse Gaussian priors. Biometrika, 99, 663-674. (pdf)
[40] Favaro, S., Lijoi, A., Prünster, I. (2012). Asymptotics for a Bayesian nonparametric estimator of species richness. Bernoulli, 18, 1267-1283 . (pdf)
[41] Favaro, S., Prünster, I., Walker, S.G. (2012). On a generalized Chu-Vandermonde identity. Methodology and Computing in Applied Probability, 14, 253-262. (pdf)
[42] Lijoi, A., Prünster, I. (2011). A conversation with Eugenio Regazzini. Statistical Science, 26, 647-672. (pdf)
[43] Favaro, S., Prünster, I., Walker, S.G. (2011). On a class of random probability measures with general predictive structure. Scandinavian Journal of Statistics, 38, 359-376. (pdf)
[44] Favaro, S., Hadjicharalambous, G., Prünster, I. (2011). On a class of distributions on the simplex. Journal of Statistical Planning and Inference, 141, 2987-3004. (pdf)
[45] James, L.F., Lijoi, A., Prünster, I. (2010). On the posterior distribution of classes of random means. Bernoulli, 16, 155-180. (pdf)
[46] Favaro, S., Lijoi A., Mena, R.H., Prünster, I. (2009). Bayesian nonparametric inference for species variety with a two parameter Poisson-Dirichlet process prior. Journal of the Royal Statistical Society Series B, 71, 993-1008. (pdf)
[47] Lijoi, A., Prünster, I. (2009). Distributional properties of means of random probability measures. Statistics Surveys, 3, 47-95. (pdf)
[48] De Blasi, P., Peccati, G., Prünster, I. (2009). Asymptotics for posterior hazards. The Annals of Statistics, 37, 1906-1945. (pdf)
[49] James, L.F., Lijoi, A., Prünster, I. (2009). Posterior analysis for normalized random measures with independent increments. Scandinavian Journal of Statistics, 36, 76-97. (pdf)
[50] Nieto-Barajas, L.E., Prünster, I. (2009). A sensitivity analysis for Bayesian nonparametric density estimators. Statistica Sinica, 19, 685-705. (pdf)
[51] Lijoi A., Mena, R.H., Prünster, I. (2008). A Bayesian Nonparametric approach for comparing clustering structures in EST libraries. Journal of Computational Biology, 15, 1315-1327. (pdf)
[52] Peccati, G., Prünster, I. (2008). Linear and quadratic functionals of random hazard rates: an asymptotic analysis. The Annals of Applied Probability, 18, 1910-1943. (pdf)
[53] Lijoi, A., Prünster, I., Walker, S.G. (2008). Posterior analysis for some classes of nonparametric models. Journal of Nonparametric Statistics, 20, 447-457. (pdf)
[54] Lijoi, A., Prünster, I., Walker, S.G. (2008). Bayesian nonparametric estimators derived from conditional Gibbs structures. The Annals of Applied Probability, 18, 1519-1547. (pdf)
[55] Lijoi, A., Prünster, I., Walker, S.G. (2008). Investigating nonparametric priors with Gibbs structure. Statistica Sinica, 18, 1653-1668. (pdf)
[56] James, L.F., Lijoi, A., Prünster, I. (2008). Distributions of linear functionals of two parameter Poisson-Dirichlet random measures. The Annals of Applied Probability, 18, 521-551. (pdf)
[57] Nardone, R., Golaszewski, S., Bergmann, J., Venturi, A., Prünster, I., Bratti, A., Ladurner, G.,Tezzon F. (2008). Motor cortex excitability changes following a lesion in the posterior columns of the cervical spinal cord. Neuroscience Letters, 434, 119-123.
[58] Lijoi A., Mena, R.H., Prünster, I. (2007). A Bayesian nonparametric method for prediction in EST analysis. BMC Bioinformatics, 8: 339. (pdf)
[59] Lijoi, A., Mena, R.H., Prünster, I. (2007). Bayesian nonparametric estimation of the probability of discovering a new species. Biometrika, 94, 769-786. (pdf)
[60] Lijoi, A., Mena, R.H., Prünster, I. (2007). Controlling the reinforcement in Bayesian nonparametric mixture models. Journal of the Royal Statistical Society Series B, 69, 715-740. (pdf)
[61] Lijoi, A., Prünster, I., Walker, S.G. (2007). On convergence rates for nonparametric posterior distributions. Australian & New Zealand Journal of Statistics, 49, 209-219. (pdf)
[62] Lijoi, A., Prünster, I., Walker, S.G. (2007). Bayesian consistency for stationary models. Econometric Theory, 23, 749-759. (pdf)
[63] Walker, S.G., Lijoi, A., Prünster, I. (2007). On rates of convergence for posterior distributions in infinite-dimensional models. The Annals of Statistics, 35, 738-746. (pdf)
[64] James, L.F., Lijoi, A., Prünster, I. (2006). Conjugacy as a distinctive feature of the Dirichlet process. Scandinavian Journal of Statistics, 33, 105-120. (pdf)
[65] Lijoi, A., Prünster, I., Walker, S.G. (2005). On consistency of nonparametric normal mixtures for Bayesian density estimation. Journal of the American Statistical Association, 100, 1292-1296. (pdf)
[66] Walker, S.G., Lijoi, A., Prünster, I. (2005). Data tracking and the understanding of Bayesian consistency. Biometrika, 92, 765-778. (pdf)
[67] Lijoi, A., Mena, R.H., Prünster, I. (2005). Hierarchical mixture modelling with normalized inverse Gaussian priors. Journal of the American Statistical Association, 100, 1278-1291. (pdf)
[68] Lijoi, A., Mena, R.H., Prünster, I. (2005). Bayesian nonparametric analysis for a generalized Dirichlet process prior. Statistical Inference for Stochastic Processes, 8, 283-309. (pdf)
[69] Nieto-Barajas, L.E., Prünster, I., Walker, S.G. (2004). Normalized Random Measures driven by Increasing Additive Processes. The Annals of Statistics, 32, 2343-2360. (pdf)
[70] Lijoi, A., Prünster, I. (2004). A note on the problem of heaps. Sankhya, 66, 234-242. (pdf)
[71] Lijoi, A., Prünster, I., Walker, S.G. (2004). Extending Doob's consistency theorem to nonparametric densities. Bernoulli, 10, 651-663. (pdf)
[72] Epifani, I., Lijoi, A., Prünster, I. (2003). Exponential functionals and means of neutral-to-the-right priors. Biometrika, 90, 791-808. (pdf)
[73] Regazzini, E., Lijoi, A., Prünster, I.(2003). Distributional results for means of normalized random measures with independent increments. The Annals of Statistics, 31, 560-585. (pdf)
Publications in monographs
[74] Lijoi, A., Prünster, I. (2010). Models beyond the Dirichlet process. In Bayesian Nonparametrics (Hjort, N.L., Holmes, C.C., Müller, P., Walker, S.G. Eds.), Cambridge University Press, 80-136. (pdf)
Conference proceedings, notes and discussions
[75] Ascolani, F., Lijoi, A. and Prünster, I. (2024). Discussion of “Route and community inference on the latent growth process of a network” by Crane and Xu. Journal of the Royal Statistical Society-Series B, forthcoming.
[76] Ascolani, F., Lijoi, A. and Prünster, I. (2023). Discussion of "Martingale Posterior Distributions" by Fong, Holmes and Walker. Journal ofthe Royal Statistical Society-Series B, 85, 1404-1405.
[77] Ascolani, F., Catalano, M., Prünster, I. (2023). Invited discussion of "Evaluating Sensitivity to the Stick-Breaking Prior in Bayesian Nonparametrics". Bayesian Analysis, 18, 340-344.
[78] Gaffi, F., Lijoi, A. and Prünster, I. (2022). Specification of the base measure of nonparametric priors via random means. Springer Proceedings in Mathematics and Statistics, Vol. 405, 91-100.
[79] Catalano, M., Lavenant, H., Lijoi, A., Prünster, I. (2022). Wasserstein distance and applications to Bayesian Nonparametrics. Proceedings of the 51st Meeting of the Italian Statistical Society, 1491-1496.
[80] Catalano, M., Lijoi, A., Prünster, I. (2021). Transport Distances on Random Vectors of Measures: Recent Advances in Bayesian Nonparametrics. In Advances in Probability and Mathematical Statistics, Springer, 59-70.
[81] Ascolani, F., Franzolini, B., Lijoi, A., Prünster, I. (2021). On the dependence structure in Bayesian nonparametric priors. Proceedings of the 50th Meeting of the Italian Statistical Society, 1219-1225.
[82] Ascolani, F., Lijoi, A., Pruenster, I. and Ruggiero, M. (2021).A framework for filtering in hidden Markov models with normalized random measures. Proceedings of the 50th Meeting of the Italian Statistical Society, 733-738.
[83] Camerlenghi, F., Lijoi, A.,Prünster, I. (2020). Bayesian nonparametric prediction with multi-sample data. Springer Proceedings in Mathematics & Statistics, Vol. 339, 113-121.
[84] Catalano, M., Lijoi, A., Prünster, I. (2019). Bayesian model comparison based on Wasserstein distances. Book of short papers SIS 2019, 167-172.
[85] Camerlenghi, F., Lijoi, A., Prünster, I. (2018). Density estimation via hierarchies of nonparametric priors. JSM Proceedings, Section on Bayesian Statistical Science, ASA, 2596-2605.
[86] Lijoi, A., Mena, R.H., Prünster, I. (2017). Discussion of "Sparse graphs using exchangeable random measures" by F. Caron and E. Fox. Journal ofthe Royal Statistical Society-Series B, 79, 1353.
[87] Camerlenghi, F., Lijoi, A., Prünster, I. (2017). On some distributional properties of hierarchical processes. JSM Proceedings, Section on Bayesian Statistical Science, ASA, 853-860.
[88] Kon Kam King, G., Arbel, J., Prünster, I. (2017). A Bayesian Nonparametric Approach to Ecological Risk Assessment. Springer Proceedings in Mathematics & Statistics, Vol. 194, 11-19.
[89] Arbel, J., Prünster, I. (2017). On the Truncation Error of a Superposed Gamma Process. Springer Proceedings in Mathematics & Statistics, Vol. 194, 151-159.
[90] Camerlenghi, F., Prünster, I., Ruggiero, M. (2016). On time Gibbs-type random probability measures. JSM Proceedings, Section on Nonparamteric Statistics, ASA, 1969-1976.
[91] Canale, A., Lijoi, A., Prünster, I. (2016). Bayesian Nonparametrics. Wiley StatsRef: Statistics Reference Online, 11pp.
[92] Gaetan, C., Padoan, S.A., Prünster, I. (2016). Comment on article by Page and Quintana. Bayesian Analysis, 11, 307-314.
[93] Kon Kam King, G, Arbel, J., Prünster, I. (2016). Bayesian Nonparametric Density Estimation in Ecotoxicology. 48e Journées de la Statistique de la SdSF, 6pp.
[94] Arbel, J. Prünster, I. (2016). Truncation error of a superposed gamma process in a decreasing order representation. NIPS Advances in Approximate Bayesian Inference Workshop, 7pp.
[95] Arbel, J., Prünster, I. (2015). Discussion of "Sequential Quasi-Monte-Carlo Sampling" by M. Gerber and N. Chopin. Journal of the Royal Statistical Society-Series B, 77, 569-560.
[96] Lijoi, A., Prünster, I. (2014). Discussion of “On simulation and properties of the stable law” byL. Devroye and L. James. Statistical Methods & Applications - Journal of the Italian Statistical Society, 23, 371-377.
[97] Lijoi, A., Nipoti, B., Prünster, I. (2014). A Bayesian nonparametric model for combining data from different experiments. Proceedings of the XLVII Meeting of the Italian Statistical Society,Vol. I, 10pp.
[98] Nava, C., Mena, R.H., Prünster, I. (2014). On Some Stationary Models: Construction and Estimation. Springer Proceedings in Mathematics & Statistics, Vol. 63, 187-191.
[99] Lijoi, A., Prünster, I., Walker, S.G. (2014). A note on “Bayesian nonparametric estimators derived from conditional Gibbs structures”. The Annals of Applied Probability, 24, 447-448.
[100] Nava, C., Mena, R.H., Prünster, I. (2013). On Stationary Markov Models: a Poisson-driven approach. Proceedings of the 8th Conference on Statistical Computing and Complex Systems - SCo 2013, 6pp.
[101] Favaro, S., Lijoi, A., Prünster, I. (2013). Correction to "A new estimator of the discovery probability". Biometrics, 69, 797.
[102] De Blasi, P., Favaro, S., Lijoi, A., Mena, R.H. and Prünster, I. (2012). Two Tales About Bayesian Nonparametric Modeling. JSM 2012 Proceedings, Section on Bayesian Statistical Science, ASA, 1696-1706.
[103 De Blasi, P., Lijoi, A., Prünster, I. (2012). Large sample properties of Gibbs-type priors. Proceedings of the XLVI Meeting of the Italian Statistical Society, Vol II, 4pp.
[104] De Blasi, P. ; Lijoi, A., Prünster, I. (2011). On consistency of Gibbs-type priors. Proceedings of the 58th World Statistics Congress of ISI, 7pp.
[105] Favaro, S., Lijoi, A., Mena, R.H., Prünster, I. (2011). On some issues related to species sampling problems. Proceedings of the 7th Conference on Statistical Computing and Complex Systems - SCo 2011, 9pp.
[106] De Blasi, P., Peccati, G., Prünster, I. (2010). On the Asymptotic Behaviour of Random Cumulative Hazards. JSM 2010 Proceedings, Section on Nonparametric Statistics, ASA, 1063-1074.
[107] Lijoi, A., Muliere, P., Prünster, I., Taddei, F. (2010). Exchangeable random partitions for statistical and economic modelling. Atti del Convegno Economia e Incertezza. EUT, 88-111.
[108] Mena, R.H., Prünster I. (2007). Alcune considerazioni sulle elezioni presidenziali messicane del 2006 (Italian). SIS-Magazine (electronic).
[109] Lijoi, A., Mena, R.H., Prünster, I. (2006). Bayesian clustering in nonparametric hierarchical mixture models. Proceedings of the XLIII Meeting of the Italian Statistical Society, Vol. I, 449-460.
[110] Prünster, I. (2005). Some issues in Bayesian Nonparamterics. JSM 2004 Proceedings, Section on Bayesian Statistical Science, ASA, 196-203.
[111] James, L.F., Lijoi, A., Prünster, I. (2004). On a class of priors for Bayesian Nonparametrics. Proceedings of the XLII Meeting of the Italian Statistical Society, 401-404.
[112] Prünster, I. (2004). Misure di probabilità aleatorie derivate da processi additivi crescenti e loro applicazione alla statistica bayesiana. Bollettino dell’Unione Matematica Italiana Sez. A, 7, 563-566.
[113] Lijoi, A., Prünster, I. (2003). On a normalized random measure with independent increments relevant to Bayesian nonparametric inference. Proceedings of the 13th European Young Statisticians Meeting, Bernoulli Society, 123-134.
[114] Epifani, I., Lijoi, A., Prünster, I. (2003). A note on the simulation of Lévy processes with a view towards applications. Proceedings of the 3rd Conference on Statistical Computing and Complex Systems - SCo 2003, 188-193.
Modificato il 18/06/2024