Publications
[2024+] Castelletti, F. & Ferrini, L. "Bayesian nonparametric mixtures of categorical directed graphs for heterogeneous causal inference", https://arxiv.org/pdf/2409.00453
[2024+] Mascaro, A. & Castelletti, F. "Bayesian causal discovery from unknown general interventions", https://arxiv.org/abs/2312.00509
[2025] Castelletti, F. & Mascaro, A. "BCDAG: An R package for Bayesian structure and Causal learning of Gaussian DAGs", accepted for publication in Journal of Statistical Software
[2024] Castelletti, F., Consonni, G. & Della Vedova, M. L. "Joint structure learning and causal effect estimation for categorical graphical models", Biometrics
[2024] Galimberti, C., Peluso, S., Castelletti, F. "Bayesian inference of graph-based dependencies from mixed-type data", Journal of Multivariate Analysis
[2024] Castelletti, F. "Learning Bayesian networks: a copula approach for mixed-type data", Psychometrika
[2024] Castelletti, F., Niro, F., Denti, M., Tessera, D. & Pozzi, A. "Bayesian learning of causal networks for unsupervised fault diagnosis in distributed energy systems", IEEE Access
[2023] Castelletti, F. & Consonni, G. "Bayesian sample size determination for causal discovery", Statistical Science
[2023] Castelletti, F. & Peluso, S. "Bayesian learning of network structures from interventional experimental data", Biometrika
[2023] Castelletti, F. & Consonni, G. "Bayesian graphical modeling for heterogeneous causal effects", Statistics in Medicine
[2022] Castelletti, F. & Peluso, S. "Network structure learning under uncertain interventions", Journal of the American Statistical Association
[2022] Castelletti, F., Consonni, G. & La Rocca, L. "Discussion to: Bayesian graphical models for modern biological applications", Statistical Methods and Applications
[2021] Castelletti, F. & Mascaro, A. "Structural learning and estimation of joint causal effects among network-dependent variables", Statistical Methods and Applications
[2021] Castelletti, F. & Peluso, S. "Equivalence class selection of categorical graphical models", Computational Statistics and Data Analysis
[2021] Castelletti, F. & Consonni, G. "Bayesian causal inference in probit graphical models", Bayesian Analysis
[2021] Castelletti, F. & Consonni, G. "Bayesian inference of causal effects from observational data in Gaussian graphical models", Biometrics
[2020] Castelletti, F., Consonni, G., La Rocca, L., Peluso, S. & Stingo, F.C. "Bayesian learning of multiple directed networks from observational data", Statistics in Medicine
[2020] Castelletti, F. "Bayesian model selection of Gaussian DAG structures", International Statistical Review
[2020] Castelletti, F. & Consonni, G.. "Discovering causal structures in Bayesian Gaussian DAG models", Journal of the Royal Statistical Society: Series A
[2019] Castelletti, F. & Consonni, G. "O'Bayes model selection of Gaussian interventional essential graphs for the identification of signaling pathways", The Annals of Applied Statistics
[2018] Castelletti, F., Consonni, G., Della Vedova, M. & Peluso, S. "Learning Markov equivalence classes of Directed Acyclic Graphs: an Objective Bayes Approach", Bayesian Analysis
[2018] Castelletti, F. & Peluso, S. "Bayesian cluster analysis: Point estimation and credible balls. Contributed discussion", Bayesian Analysis