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IGOR PRÜNSTER

Papers

Articles in peer-reviewed Journals

[1] Lijoi, A., Prünster, I., Rigon, T. (2020). The Pitman-Yor multinomial model for mixture modelling. Biometrika, forthcoming.  (pdf)

[2] Camerlenghi, F., Lijoi, A., Prünster, I. (2020). Survival analysis via hierarchically dependent mixture hazards. The Annals of Statistics, forthcoming.  (pdf)

[3] Catalano, M., Lijoi, A., Prünster, I. (2020). Approximation of Bayesian models for time-to-event data. Electronic Journal of Statistics, 14, 3366-3395.   (pdf)

[4] Lijoi, A., Prünster, I., Rigon, T. (2020). Sampling hierarchies of discrete random structures. Statistics and Computing, 30, 1591-1607.  (pdf)   

[5] 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)

[6] 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)

[7] Camerlenghi, F., Dunson, D.B.., Lijoi, A., Prünster, I., Rodriguez, A. (2019). Latent nested nonparametric priors (with discussion). Bayesian Analysis, 15, 1303-1356.  (pdf)

[8] Camerlenghi, F., Lijoi, A., Orbanz, P., Prünster, I. (2019). Distribution theory for hierarchical process. The Annals of Statistics, 47, 67-92. (pdf)

[9] Arbel, J., De Blasi, P., Prünster, I. (2019). Stochastic approximations to the Pitman-Yor process. Bayesian Analysis, 15, 1201-1219. (pdf)

[10] Camerlenghi, F., Lijoi, A., Prünster, I. (2018). Bayesian nonparametric inference beyond the Gibbs-type framework. Scandinavian Journal of Statistics, 45, 1062-1091. (pdf)

[11] Anzarut, M., Mena, R.H., Nava, C., Prünster, I. (2018). Poisson driven stationary Markov models. Journal of Business and Economic Statistics, 36, 684-694. (pdf)

[12] 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)

[13] Camerlenghi, F., Lijoi, A., Prünster, I. (2017). Bayesian prediction with multiple-samples information. Journal of Multivariariate Analysis, 156, 18-28. (pdf)

[14] Canale, A., Prünster, I. (2017). Robustifying Bayesian nonparametric mixtures for count data. Biometrics, 73, 174-184. (pdf)

[15] Arbel, J., Prünster, I. (2017). A moment-matching Ferguson & Klass algortihm. Statistics and Computing, 27, 3-17. (pdf)

[16] 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)

[17] 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)

[18] 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)

[19] 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)

[20] Lijoi, A., Nipoti, B., Prünster, I. (2014). Bayesian inference with dependent normalized completely random measures. Bernoulli, 20, 1260-1291. (pdf)

[21] Lijoi, A., Nipoti, B., Prünster, I. (2014). Dependent mixture models: clustering and borrowing information. Computational Statistics & Data Analysis, 71, 417-433. (pdf)

[22] Barrios, E., Lijoi, A., Nieto-Barajas, L.E., Prünster, I. (2013). Modeling with normalized random measure mixture models. Statistical Science, 28, 313-334. (pdf)

[23] Favaro, S., Lijoi, A., Prünster, I. (2013). Conditional formulae for Gibbs-type exchangeable random partitions. The Annals of Applied Probability, 23, 1721-1754. (pdf)

[24] De Blasi, P., Lijoi, A., Prünster, I. (2013). An asymptotic analysis of a class of discrete nonparametric priors. Statistica Sinica, 23, 1299-1322. (pdf)

[25] Prünster, I., Ruggiero, M. (2013). A Bayesian nonparametric approach to modeling market share dynamics. Bernoulli, 19, 64-92. (pdf)

[26] Favaro, S., Lijoi, A., Prünster, I. (2012). A new estimator of the discovery probability. Biometrics, 68, 1188-1196. (pdf with a minor correction)

[27] Favaro, S., Lijoi, A., Prünster, I. (2012). On the stick-breaking representation of normalized inverse Gaussian priors. Biometrika, 99, 663-674. (pdf)

[28] Favaro, S., Lijoi, A., Prünster, I. (2012). Asymptotics for a Bayesian nonparametric estimator of species richness. Bernoulli, 18, 1267-1283 . (pdf)

[29] Favaro, S., Prünster, I., Walker, S.G. (2012). On a generalized Chu-Vandermonde identity. Methodology and Computing in Applied Probability, 14, 253-262. (pdf)

[30] Lijoi, A., Prünster, I. (2011). A conversation with Eugenio Regazzini. Statistical Science, 26, 647-672. (pdf)

[31] 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)

[32] 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)

[33] James, L.F., Lijoi, A., Prünster, I. (2010). On the posterior distribution of classes of random means. Bernoulli, 16, 155-180. (pdf)

[34] 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)

[35] Lijoi, A., Prünster, I. (2009). Distributional properties of means of random probability measures. Statistics Surveys, 3, 47-95. (pdf)

[36] De Blasi, P., Peccati, G., Prünster, I. (2009). Asymptotics for posterior hazards. The Annals of Statistics, 37, 1906-1945. (pdf)

[37] 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)

[38] Nieto-Barajas, L.E., Prünster, I. (2009). A sensitivity analysis for Bayesian nonparametric density estimators. Statistica Sinica, 19, 685-705. (pdf)

[39] 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)

[40] 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)

[41] Lijoi, A., Prünster, I., Walker, S.G. (2008). Posterior analysis for some classes of nonparametric models. Journal of Nonparametric Statistics, 20, 447-457. (pdf)

[42] 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)

[43] Lijoi, A., Prünster, I., Walker, S.G. (2008). Investigating nonparametric priors with Gibbs structure. Statistica Sinica, 18, 1653-1668. (pdf)

[44] 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)

[45] 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.

[46] Lijoi A., Mena, R.H., Prünster, I. (2007). A Bayesian nonparametric method for prediction in EST analysis. BMC Bioinformatics, 8: 339. (pdf)

[47] Lijoi, A., Mena, R.H., Prünster, I. (2007). Bayesian nonparametric estimation of the probability of discovering a new species. Biometrika, 94, 769-786. (pdf)

[48] 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)

[49] 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)

[50] Lijoi, A., Prünster, I., Walker, S.G. (2007). Bayesian consistency for stationary models. Econometric Theory, 23, 749-759. (pdf)

[51] 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)

[52] 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)

[53] 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)

[54] Walker, S.G., Lijoi, A., Prünster, I. (2005). Data tracking and the understanding of Bayesian consistency. Biometrika, 92, 765-778. (pdf)

[55] 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)

[56] 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)

[57] 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)

[58] Lijoi, A., Prünster, I. (2004). A note on the problem of heaps. Sankhya, 66, 234-242. (pdf)

[59] Lijoi, A., Prünster, I., Walker, S.G. (2004). Extending Doob's consistency theorem to nonparametric densities. Bernoulli, 10, 651-663. (pdf)

[60] Epifani, I., Lijoi, A., Prünster, I. (2003). Exponential functionals and means of neutral-to-the-right priors. Biometrika, 90, 791-808. (pdf)

[61] 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

[62] 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

[63] Catalano, M., Lijoi, A., Prünster, I. (2020). Transport Distances on Random Vectors of Measures: Recent Advances in Bayesian Nonparametrics. Proceedings of XV Latin American Congress of Probability and Mathematical Statistics (CLAPEM), Birkhäuser, forthcoming. 

[64] Catalano, M., Lijoi, A., Prünster, I. (2019). Bayesian model comparison based on Wasserstein distances. Book of short papers SIS 2019, 167-172.

[65] Camerlenghi, F., Lijoi, A., Prünster, I. (2019). Bayesian nonparametric prediction with multi-sample data. ISNPS 2018 Proceedings, Springer, forthcoming.

[66] Camerlenghi, F., Lijoi, A., Prünster, I. (2018). Density estimation via hierarchies of nonparametric priors. JSM Proceedings, Section on Bayesian Statistical Science, ASA, 2596-2605.

[67] Lijoi, A., Mena, R.H., Prünster, I. (2017). Discussion of "Sparse graphs using exchangeable random measures" by F. Caron and E. Fox. Journal of the Royal Statistical Society-Series B, 79, 1353.

[68] Camerlenghi, F., Lijoi, A., Prünster, I. (2017). On some distributional properties of hierarchical processes. JSM Proceedings, Section on Bayesian Statistical Science, ASA, 853-860.

[69] Kon Kam King, G., Arbel, J., Prünster, I. (2017). A Bayesian Nonparametric Approach to Ecological Risk Assessment. Springer Proceedings in Mathematics and Statistics, Vol. 194, 11-19.

[70] Arbel, J., Prünster, I. (2017). On the Truncation Error of a Superposed Gamma Process. Springer Proceedings in Mathematics and Statistics, Vol. 194, 151-159.

[71] Camerlenghi, F., Prünster, I., Ruggiero, M. (2016). On time Gibbs-type random probability measures. JSM Proceedings, Section on Nonparamteric Statistics, ASA, 1969-1976.

[72] Canale, A., Lijoi, A., Prünster, I. (2016). Bayesian Nonparametrics. Wiley StatsRef: Statistics Reference Online, 11pp.

[73] Gaetan, C. Padoan, S.A., Prünster, I. (2016). Comment on article by Page and Quintana. Bayesian Analysis, 11, 307-314.

[74] Kon Kam King, G, Arbel, J., Prünster, I. (2016). Bayesian Nonparametric Density Estimation in Ecotoxicology. 48e Journées de la Statistique de la SdSF, 6pp.

[75] 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.

[76] 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.

[77] Lijoi, A., Prünster, I. (2014). Discussion of “On simulation and properties of the stable law” by L. Devroye and L. James. Statistical Methods & Applications - Journal of the Italian Statistical Society, 23, 371-377.

[78] 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.

[79] Nava, C., Mena, R.H., Prünster, I. (2014). On Some Stationary Models: Construction and Estimation. Springer Proceedings in Mathematics and Statistics, Vol. 63, 187-191.

[80] 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.

[81] 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.

[82] Favaro, S., Lijoi, A., Prünster, I. (2013). Correction to "A new estimator of the discovery probability". Biometrics, 69, 797.

[83] De Blasi, P., Favaro, S., Lijoi, A., Mena, R.H., Prünster, I. (2012). Two Tales About Bayesian Nonparametric Modeling. JSM Proceedings, Section on Bayesian Statistical Science, ASA, 1696-1706.

[84] De Blasi, P., Lijoi, A., Prünster, I. (2012). Large sample properties of Gibbs-type priors. Proceedings of XLVI Meeting of the Italian Statistical Society, Vol II, 4pp.

[85] De Blasi, P., Lijoi, A., Prünster, I. (2011). On consistency of Gibbs-type priors. Proceedings of the 58th World Statistics Congress of ISI, 7pp.

[86] 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 (electronic).

[87] De Blasi, P., Peccati, G., Prünster, I. (2010). On the asymptotic behaviour of random cumulative hazards. JSM Proceedings, Section on Nonparamteric Statistics, ASA, 1063-1074.

[88] Lijoi, A., Muliere, P., Prünster, I.,Taddei, F. (2010). Exchangeable random partitions for statistical and economic modelling. Proceedings of the Conference on Economics and Uncertainty, Trieste, 85-111.

[89] Mena, R.H., Prünster, I. (2007). Alcune considerazioni sulle elezioni presidenziali messicane del 2006. SIS Magazine (electronic).

[90] Lijoi, A., Mena, R.H., Prünster, I. (2006). Bayesian clustering in nonparametrics hierarchical mixture models. Proceedings of XLIII Meeting of the Italian Statistical Society, Vol. I, 449-460.

[91] Prünster, I. (2005). Some issues in Bayesian Nonparametrics. JSM Proceedings, Section on Bayesian Statistical Science, Alexandria, ASA, 196-203.

[92] Prünster, I. (2004). Misure di probabilità aleatorie derivate da processi additivi crescenti e loro applicazione alla statistica bayesiana. Bollettino U.M.I. Sez. A, 7, 563-566.

[93] 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.

[94] 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.

[95] E

Modificato il 02/10/2020