Articles in refereed journals

  • Denti F. and D’Angelo L. (2025) The generalized nested common atoms model. Econometrics and Statistics, 1–28 (in press). DOI: 10.1016/j.ecosta.2025.01.001.
    Article - Citation

  • D’Angelo L. and Denti F. (2024) A finite-infinite shared atoms nested model for the Bayesian analysis of large grouped data. Bayesian Analysis, 1–34 (in press). DOI: 10.1214/24-BA1458.
    Article - Citation

  • D’Angelo L. and Canale A. (2023) Efficient posterior sampling for Bayesian Poisson regression. Journal of Computational and Graphical Statistics, 32(3), 917–926. DOI: 10.1080/10618600.2022.2123337.
    Article - Citation

  • D’Angelo L., Canale A., Yu Z. and Guindani M. (2023) Bayesian nonparametric analysis for the detection of spikes in noisy calcium imaging data. Biometrics, 79(2), 1370–1382. DOI: 10.1111/biom.13626.
    Article - Citation



Ph.D. Thesis

  • D’Angelo L. (2022) Bayesian modeling of calcium imaging data (PhD Thesis).
    Supervisor: Prof. Antonio Canale; Co-supervisor: Prof. Michele Guindani.
    Research Padua Archive - Full text - Citation


Conference proceedings and discussions

  • D’Angelo L., Nipoti B. and Ongaro A. (2024) Two-level clustering of patients and hospitals via thinned dependent Dirichlet process mixtures. In Methodological and Applied Statistics and Demography II, Conference proceedings of SIS 2024, Springer (in press).

  • D’Angelo L. (2025) Exploring the challenges of the analysis of the Allen Brain Observatory dataset. In Advances in Neural Data Science, Proceedings of the Data Research Camp 2022, Venice, Italy; Springer, 1–11.

  • D’Angelo L. (2023) A comparison of computational approaches for posterior inference in Bayesian Poisson regression, in Book of Short Papers SIS 2023, 903–907.

  • D’Angelo L. and Denti, F. (2023) Bayesian analysis of Amazon’s best-selling books via finite nested mixture models, in Book of Short Papers SIS 2023, 1117–1120.

  • D’Angelo L. (2022) Bayesian nonparametric clustering of spatially-referenced spike train data, in Book of Short Papers SIS 2022, 514–519.

  • Denti F., D’Angelo L. and Guindani M. (2022) Bayesian approaches for capturing the heterogeneity of neuroimaging experiments, in Book of Short Papers SIS 2022, 18–29.

  • D’Angelo L. and Canale A. (2021) Contributed Discussion on: “Centered Partition Processes: Informative Priors for Clustering”, in Bayesian Analysis, 16(1), 356–358.

  • D’Angelo L., Canale A., Yu Z. and Guindani M. (2021) Detection of neural activity in calcium imaging data via Bayesian mixture models, in Book of Short Papers SIS 2021, 745–750.

  • D’Angelo L. (2019) Model based clustering in group life insurance via Bayesian nonparametric mixtures, in Book of Short Papers SIS 2019.


Software

  • D’Angelo L. and Denti F. (2023) “SANple: Fitting Shared Atoms Nested Models via Markov Chains Monte Carlo”, R package.
    CRAN - Github

  • Denti F. and D’Angelo L. (2023) “SANvi: Fitting Shared Atoms Nested Models via Variational Bayes”, R package.
    CRAN - Github

  • D’Angelo L. (2021) “bpr: Fitting Bayesian Poisson Regression”, R package.
    CRAN - Github