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IGOR PRÜNSTER

Papers

Articles in refereed Journals

[1] Canale, A., Lijoi, A., Nipoti, B. and Prünster, I. (2017). On the Pitman-Yor process with spike and slab base measure. Biometrika, forthcoming.  (pdf)

[2] Camerlenghi, F., Lijoi, A. and Prünster, I. (2017). Bayesian prediction with multiple-samples informationJournal of Multivariariate Analysis156, 18-28.  (pdf)   

[3] Anzarut, M., Mena, R.H., Nava, C. and Prünster, I. (2017). Poisson driven stationary Markov models. Journal of Business and Economic Statistics, forthcoming. (pdf)

[4] Canale, A. and  Prünster, I. (2017). Robustifying Bayesian nonparametric mixtures for count dataBiometrics, 73, 174-184. (pdf)

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

[6] Lijoi, A., Muliere, P., Prünster, I. and Taddei, F. (2016). Innovation, growth and aggregate volatility from a Bayesian nonparametric perspective. Electronic Journal of Statistics, 10, 2179-2203.  (pdf)

[7] Favaro, S., Lijoi, A., Nava, C., Nipoti, B., Prünster, I. and Teh, Y.W. (2016). On the stick-breaking representation for homogeneous NRMIs. Bayesian Analysis, 11, 697-724.  (pdf)

[8] De Blasi, P., Favaro, S., Lijoi, A., Mena, R., Prünster, I. and 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)

[9] 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)

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

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

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

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

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

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

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

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

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

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

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

[21] Favaro, S., Prünster, I., and Walker, S.G. (2011). On a class of random probability measures with general predictive structure. Scandinavian Journal of Statistics, 38, 359-376.   (pdf)

[22] Favaro, S., Hadjicharalambous, G. and Prünster, I. (2011). On a class of distributions on the simplex. Journal of Statistical Planning and Inference, 141, 2987-3004.   (pdf)

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

[24] Favaro, S., Lijoi A., Mena, R.H., and 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)

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

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

[27] James, L.F., Lijoi, A., and Prünster, I. (2009). Posterior analysis for normalized random measures with independent increments. Scandinavian Journal of Statistics, 36, 76-97.   (pdf)

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

[29] Lijoi A., Mena, R.H., and Prünster, I. (2008). A Bayesian Nonparametric approach for comparing clustering structures in EST libraries. Journal of Computational Biology, 15, 1315-1327.  (pdf)

[30] Peccati, G. and Prünster, I. (2008). Linear and quadratic functionals of random hazard rates: an asymptotic analysis. The Annals of Applied Probability, 18, 1910-1943.  (pdf)

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

[32] Lijoi, A., Prünster, I., and Walker, S.G. (2008). Bayesian nonparametric estimators derived from conditional Gibbs structures. The Annals of Applied Probability, 18, 1519-1547.  (pdf)

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

[34] James, L.F., Lijoi, A., and Prünster, I. (2008). Distributions of linear functionals of two parameter Poisson-Dirichlet random measures. The Annals of Applied Probability, 18, 521-551.  (pdf)

[35] Nardone, R., Golaszewski, S., Bergmann, J., Venturi, A., Prünster, I., Bratti, A., Ladurner, G. and Tezzon F. (2008). Motor cortex excitability changes following a lesion in the posterior columns of the cervical spinal cord. Neuroscience Letters, 434, 119-123.  

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

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

[38] Lijoi, A., Mena, R.H., and Prünster, I. (2007). Controlling the reinforcement in Bayesian nonparametric mixture models. Journal of the Royal Statistical Society Series B, 69, 715-740.  (pdf)

[39] Lijoi, A., Prünster, I., and Walker, S.G. (2007). On convergence rates for nonparametric posterior distributions. Australian & New Zealand Journal of Statistics, 49, 209-219.  (pdf)

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

[41] 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)

[42] James, L.F., Lijoi, A., and Prünster, I. (2006). Conjugacy as a distinctive feature of the Dirichlet process. Scandinavian Journal of Statistics, 33, 105-120.  (pdf)

[43] Lijoi, A., Prünster, I, and Walker, S.G. (2005). On consistency of nonparametric normal mixtures for Bayesian density estimation. Journal of the American Statistical Association, 100, 1292-1296.  (pdf)

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

[45] Lijoi, A., Mena, R.H., and Prünster, I. (2005). Hierarchical mixture modelling with normalized inverse Gaussian priors. Journal of the American Statistical Association, 100, 1278-1291.  (pdf)

[46] Lijoi, A., Mena, R.H., and Prünster, I. (2005). Bayesian nonparametric analysis for a generalized Dirichlet process prior. Statistical Inference for Stochastic Processes, 8, 283-309.  (pdf)

[47] Nieto-Barajas, L.E., Prünster, I, and Walker, S.G. (2004). Normalized Random Measures driven by Increasing Additive Processes. The Annals of Statistics, 32, 2343-2360.  (pdf)

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

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

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

[51] Regazzini, E., Lijoi, A. and 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

[52] Lijoi, A. and 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

[53] Lijoi, A., Mena, R.H. and 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, forthcoming

[54] 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.

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

[56] Camerlenghi, F., Prünster, I. and Ruggiero, M. (2016). On time Gibbs-type random probability measures. JSM Proceedings, Section on Nonparamteric Statistics, Alexandria, VA: American Statistical Association, 1969-1976.

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

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

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

[60] 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.

[61] 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.

[62] 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.

[63] 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.

[64] 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.

[65] Nava, C., Mena, R.H., and 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 (electronic).

[66] De Blasi, P., Favaro, S., Lijoi, A., Mena, R.H., and Prünster, I. (2012). Two Tales About Bayesian Nonparametric Modeling. JSM Proceedings, Section on Bayesian Statistical Science. Alexandria, VA: American Statistical Association, 1696-1706.

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

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

[69] Favaro, S., Lijoi A., Mena, R.H., and 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).

[70] De Blasi, P., Peccati, G. and Prünster, I. (2010). On the asymptotic behaviour of random cumulative hazards. JSM Proceedings, Section on Nonparamteric Statistics, Alexandria, VA: American Statistical Association, 1063-1074.

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

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

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

[74] Prünster, I. (2005). Some issues in Bayesian Nonparamterics. JSM Proceedings, Section on Bayesian Statistical Science, Alexandria, VA: American Statistical Association, 196-203.

[75] 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.

[76] James, L.F., Lijoi, A., and Prünster, I. (2004). On a class of priors for Bayesian Nonparametrics. Proceedings of XLII Meeting of the Italian Statistical Society, Vol. II, 401-404.

[77] Lijoi, A. and 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.

[78] Epifani, I., Lijoi, A., and Prunster, I. (2003). A note on the simulation of Lévy processes with a view towards applications. Proceedings of S.Co. 2003, 188-193.

 

Last change 02/07/2017