The order of the authors is alphabetical in all publications but those indicated by a star *

Publications in refereed journals

1. Nipoti, B. & Schiavon, L. (2024)
   Expected goals under a Bayesian viewpoint: uncertainty quantification and online learning
   Journal of Quantitative Analysis in Sport, to appear

2. Hernández, B., Dyer, A.H., Finucane, C., Nipoti, B., Romero-Ortuno, R., Reilly, R. & Kenny, R.A. (2024) *
   The Impact of Type 2 Diabetes on Peripheral and Cerebral Haemodynamic Responses to Active Stand
   Journal of Gerontology: Medical Sciences, 79(5), p.glae073.

3. Schiavon, L., Canale, A. & Nipoti, B. (2024) *
   Accelerated structured matrix factorization
   Journal of Computational and Graphical Statistics, pp.1-11 (ArXiv)

4. Canale, A., Lijoi A., Nipoti, B. & Pruenster, I. (2023)
   Inner spike and slab Bayesian nonparametric models
   Econometrics and Statistics (Part B: Statistics), 27, 120-135 (ArXiv)

5. Bissiri, P.G., Cleanthous, G., Emery, X.M., Nipoti, B. & Porcu, E. (2022)
   Nonparametric Bayesian modelling of longitudinally integrated covariance functions on spheres
   Computational Statistics & Data Analysis, 176, 107555

6. Canale, A., Corradin, R. & Nipoti, B. (2022)
   Importance conditional sampler for Pitman-Yor mixtures
   Statistics and Computing, 32(40), 1-18  (ArXiv)

7. Corradin, R., Nieto-Barajas, L.E. & Nipoti, B. (2022)
   Optimal stratification of survival data via Bayesian nonparametric mixtures
   Econometrics and Statistics (Part B: Statistics), 22, 17-39 (ArXiv)

8. Corradin, R., Canale, A. & Nipoti, B. (2021) *
   BNPmix: an R package for Bayesian nonparametric modelling via Pitman-Yor mixtures
   Journal of Statistical Software, 100(15), 1-33 (R package)

9. Arbel, J., Corradin, R. & Nipoti, B. (2021)
   Dirichlet process mixtures under affine transformations of the data
   Computational Statistics, 36(1), 577-601 (ArXiv)

10. Arbel, J., Marchal, O. & Nipoti, B. (2020)
    On the Hurwitz zeta function with an application to the beta-exponential distribution
    Journal of Inequalities and Applications, 89. (pdf, ArXiv)

11. Nipoti, B., Jara, A. & Guindani, M. (2018) *
    A Bayesian semiparametric partially PH model for clustered time-to-event data
    Scandinavian Journal of Statistics, 45, 1016-1035. (pdf 1,pdf 2)

12. Nipoti, B & Shen, W. (2018)
    Contributed comment on Wade and Ghahramani's article
    Bayesian Analysis, 13(2), 613-615.

13. Canale, A., Lijoi, A., Nipoti, B. & Pruenster, I. (2017)
    On the Pitman-Yor process with spike and slab base measure
    Biometrika, 104(3), 681-697. (pdf)

14. Arbel, J., Favaro, S., Nipoti, B. & Teh, Y.W. (2017)
    Bayesian nonparametric inference for discovery probabilities: credible intervals and large sample asymptotics
    Statistica Sinica, 27(2), 839-858. (ArXiv)

15. Favaro, S., Lijoi, A., Nava, C., Nipoti, B., Pruenster, I. & Teh, Y.W. (2016)
    On the stick-breaking representation for homogeneous NRMIs
    Bayesian Analysis, 11(3), 697-724.

16. Favaro, S., Nipoti, B. & Teh, Y.W. (2016)
    Rediscovery of Good-Turing estimators via Bayesian nonparametrics
    Biometrics, 72, 136-145. (ArXiv)

17. Arbel, J., Lijoi, A. & Nipoti, B. (2016)
    Full Bayesian inference with hazard mixture models
    Computational Statistics & Data Analysis, 93, 359-372. (ArXiv)

18. Favaro, S. Nipoti, B. & Teh, Y.W. (2015)
    Random variate generation for Laguerre-type exponentially tilted α-stable distributions
    Electronic Journal of Statistics, 9, 1230-1242.

19. Favaro, S., Lomeli, M., Nipoti, B. & Teh, Y.W. (2014)
    On the stick-breaking representation of σ-stable Poisson-Kingman models
    Electronic Journal of Statistics, 8, 1063-1085.

20. Favaro, S. & Nipoti, B. (2014)
    Discussion of "On simulation and properties of the stable law" by L. Devroy and L. James"
    Statistical Methods & Applications, 23(3), 365-369.

21. Cesari, O., Favaro, S. & Nipoti, B. (2014)
    Posterior analysis of rare variants in Gibbs-type species sampling models
    Journal of Multivariate Analysis, 231, 79-98.

22. Lijoi, A. & Nipoti, B. (2014)
    A class of hazard rate mixtures for combining survival data from different experiments
    Journal of the American Statistical Association, 109, 802-814.

23. Lijoi, A., Nipoti, B. & Pruenster, I. (2014)
    Bayesian inference with dependent normalized completely random measures
    Bernoulli, 20(3), 1260-1291. (ArXiv)

24. Lijoi, A., Nipoti, B. & Pruenster, I. (2014)
    Dependent mixture models: clustering and borrowing information
    Computational Statistics & Data Analysis, 71, 417-433.

25. Arbel, J. & Nipoti, B. (2013)
    Discussion on Müller and Mitra's "Bayesian Nonparametric Inference - Why and How"
    Bayesian Analysis, 8, 326-328.

26. Ricca, R.L. & Nipoti, B. (2011) *
    Gauss' linking number revisited
    Journal of Knot Theory and Its Ramifications, 20, 1325-1343.

Books and chapters in books

27. Arbel, J., Lijoi, A. & Nipoti, B. (2015)
    Bayesian Survival Model based on Moment Characterization
    In Proceedings of Baysm 2014. Springer proceedings in Mathematics & Statistics, 126, 3-14. (ArXiv)

28. Nipoti, B. (2012)
    Dependent Completely Random Measures and Statistical Applications
    Best Ph.D. thesis in statistics and applications. CLEUP.

29. Ricca, R.L. & Nipoti, B. (2011) *
    Derivation and Interpretation of the Gauss Linking Number
    In Introductory Lectures on Knot Theory (KauffmanL.H., Lambropoulou S., Jablan S., Przytycki J.H., eds), 428-501, Series on Knots and Everything, World Scientific Press.

Other publications

30. Barile, F., Lunagomez, S. & Nipoti, B. (2024)
    Clustereing multiple networks data with an application to the EU food trade market
    Proceedings of 2024 Conference of the Italian Statistical Society. To appear.

31. D'Angelo, L., Ongaro, A., & Nipoti, B. (2024)
    Two-level clustering of patients and hospitals via thinned dependent Dirichlet process mixtures
    Proceedings of 2024 Conference of the Italian Statistical Society. To appear.

32. Corradin, R., Nieto-Barajas, L. & Nipoti, B. (2020)
    Pitman-Yor mixtures for survival data stratification.
    Proceedings of 2020 Conference of the Italian Statistical Society.

33. Canale, A., Corradin, R. & Nipoti, B. (2019)
    Galaxy color distribution estimation via dependent nonparametric mixtures
    Proceedings of 2019 Conference of the Italian Statistical Society. (pdf)

34. Arbel, J., Favaro, S., Nipoti, B. & Teh, Y.W. (2016)
    On Bayesian nonparametric inference for discovery probabilities
    Proceedings of the 49th Scientific Meeting of the Italian Statistical Society.

35. Arbel, J., Favaro, S., Nipoti, B. & Teh, Y.W. (2016)
    Discovery Probabilities when Uncertainty Matters.
    48e Journées de la Statistique de la SFdS.

36. Lijoi, A., Nipoti, B. & Pruenster, I. (2015)
    A Bayesian nonparametric model for clustering and borrowing information
    Proceedings of 10th scientific Meeting of the Classification and Data Analysis Group.

37. Favaro, S., Nipoti, B. & Teh, Y.W. (2015)
    On a class of smoothed Good-Turing estimators
    Proceedings of the SIS2015 Statistical Conference.

38. Favaro, S. & Nipoti, B. (2014)
    Uncertainty quantification for Bayesian nonparametric estimators of rare species variety
    Proceedings of the 47th Scientific Meeting of the Italian Statistical Society.

39. Lijoi, A., Nipoti, B. & Pruenster, I. (2014)
    A Bayesian nonparametric model for combining data from different experiments
    Proceedings of the 47th Scientific Meeting of the Italian Statistical Society.

40. Favaro, S., Lomeli, M., Nipoti, B. & Teh, Y.W. (2013)
    Stick-breaking representations of 1/2-stable Poisson-Kingman models
    Proceedings S.Co 2013.

41. Lijoi, A. & Nipoti, B. (2012)
    Two classes of bivariate distributions on the unit square (pdf)
    Technical report - Carlo Alberto Notebooks.

Software

• BNPmix (R package, CRAN link). Corradin, R. [aut,cre], Canale, A. [ctb] & Nipoti, B. [ctb] (2019)

In preparation or submitted

• Modelling the distribution of bugs across software releases via dependent neutral-to-the-right priors (with F. Donaghy, A. Lijoi and S. Wilson, in preparation)

• On the support of nonparametric mixture models for survival data (with A. Jara, in preparation)

• Full Bayesian inference with dependent normalized completely random measures (with F. Camerlenghi, A. Lijoi and I. Pruenster, in preparation) 

• Bayesian functional mixture modelling to uncover distinct neurocardiovascular profiles in older Irish adults (with B. Hernandez, R.A. Kenny, R.B. Reilly, in preparation)