Riccardo Corradin

Contact

• workRoom B50c School of Mathematical Sciences
  University Park
  Nottingham
  NG7 2RD
  UK
• work0115 9514930
• Riccardo.Corradin@nottingham.ac.uk
• https://rcorradin.github.io/

Biography

Riccardo joined the University of Nottingham in January 2022 as Assistant professor. Previously he was a Postdoctoral Researcher Associate at the University of Milano-Bicocca (2019-2021) with Prof. Andrea Ongaro.

Riccardo has a BSc in Statistics at the University of Milano-Bicocca (2009-2012) and a MSc in Statistics at the University of Padua (2013-2015). He has a PhD in Statistics at the University of Milano-Bicocca (2015-2019) with Prof. Bernardo Nipoti, and he was a visiting PhD student at the Trinity College of Dublin (2017-2018).

Expertise Summary

Riccardo interests are mainly on Bayesian statistics, with a focus on Bayesian nonparametric. He is interested in methodological and theoretical aspects of Bayesian statistics, computational statistics within the Bayesian field, and applications.

Recent Publications

• FEDERICO CAMERLENGHI, RICCARDO CORRADIN and ANDREA ONGARO, 2023. Contaminated Gibbs-Type Priors Bayesian Analysis. 1 - 30
• CORRADIN, RICCARDO, NIETO-BARAJAS, LUIS ENRIQUE and NIPOTI, BERNARDO, 2022. Optimal stratification of survival data via Bayesian nonparametric mixtures Econometrics and Statistics. 22, 17-38
• CORRADIN, RICCARDO, DANESE, LUCA and ONGARO, ANDREA, 2022. Bayesian nonparametric change point detection for multivariate time series with missing observations International Journal of Approximate Reasoning. 143, 26-43
• ANTONIO CANALE, RICCARDO CORRADIN and BERNARDO NIPOTI, 2022. Importance conditional sampling for Pitman–Yor mixtures Statistics and Computing. 32(3),

• View all publications

• FEDERICO CAMERLENGHI, RICCARDO CORRADIN and ANDREA ONGARO, 2023. Contaminated Gibbs-Type Priors Bayesian Analysis. 1 - 30
• CORRADIN, RICCARDO, NIETO-BARAJAS, LUIS ENRIQUE and NIPOTI, BERNARDO, 2022. Optimal stratification of survival data via Bayesian nonparametric mixtures Econometrics and Statistics. 22, 17-38
• CORRADIN, RICCARDO, DANESE, LUCA and ONGARO, ANDREA, 2022. Bayesian nonparametric change point detection for multivariate time series with missing observations International Journal of Approximate Reasoning. 143, 26-43
• ANTONIO CANALE, RICCARDO CORRADIN and BERNARDO NIPOTI, 2022. Importance conditional sampling for Pitman–Yor mixtures Statistics and Computing. 32(3),
• ARBEL, JULYAN, CORRADIN, RICCARDO and NIPOTI, BERNARDO, 2021. Dirichlet process mixtures under affine transformations of the data Computational Statistics. 36, 577–601
• CORRADIN, RICCARDO, CANALE, ANTONIO and NIPOTI, BERNARDO, 2021. BNPmix: an R package for Bayesian nonparametric modelling via Pitman-Yor mixtures Journal of Statistical Software. 100(15), 1-33
• BOSCARI, ELISA, PUJOLAR, JOSE MARTIN, DUPANLOUP, ISABELLE, CORRADIN, RICCARDO and CONGIU, LEONARDO, 2014. Captive Breeding Programs Based on Family Groups in Polyploid Sturgeons PLOS ONE. 9(10), 1-10