Publications

Amir Khorrami Chokami, Silvia Montagna. Joint Complete Records occurrence over Farlie-Gumbel-Morgenstern sequences. In Book of Short Papers SIS 2024, 2024.

Silvia Montagna, Amir Khorrami Chokami, Surya T. Tokdar. Detecting Circadian Gene Expressions via Bayesian Analysis: an Application to the Arabidopsis Thaliana Dataset. In Book of Short Papers SIS 2024, 2024.

Maddalena Cavicchioli, Fabio Demaria, Maria Franco Villoria, Patrizio Frederic, Maria Cristiana Martini, Silvia Montagna, Isabella Morlini. Statistica: dalla datificazione dei processi alla previsione. ISBN: 978-88-89427-05-7, 2024.

Raffaele Argiento, Alessandro Colombi, Lorenzo Modotti, Silvia Montagna. Clustering athlete performances in track and field sports. In Book of Short Papers IES 2023, 2023.

Marco Dalla Pria, Silvia Montagna. The hierarchical Beta-Bernoulli process as out-of-scope query detector. In Book of Short Papers SIS 2023, 2023.

Claudia Berloco, Raffaele Argiento, Silvia Montagna. Forecasting short-term defaults of firms in a commercial network via Bayesian spatial and spatio-temporal methods. In International Journal of Forecasting, 2023.

Patric Dolmeta, Raffaele Argiento, Silvia Montagna. Bayesian GARCH Modeling of Functional Sports Data. In Statistical Methods & Applications, 2023.

Patric Dolmeta, Raffaele Argiento, Silvia Montagna. Bayesian functional mixed effects model for sports data. In Book of Short Papers SIS 2022, 2022.

Claudia Berloco, Raffaele Argiento, Silvia Montagna. Predictive power of Bayesian CAR models on scale free networks: an application for credit risk. In Cladag 2021 Book of Abstracts and Short Papers, 2021.

Federico Marotta, Paolo Provero, Silvia Montagna. Prediction of gene expression from transcription factors affinities: an application of Bayesian non-linear modelling. In Cladag 2021 Book of Abstracts and Short Papers, 2021.

Silvia Montagna, Vanessa Orani, Raffaele Argiento. Bayesian isotonic logistic regression via constrained splines: an application to estimating the serve advantage in professional tennis. In Statistical Methods & Applications, 2021.

Pantelis Samartsidis, Sean Seaman, Silvia Montagna, André Charlett, Matthew Hickman, Daniela De Angelis. A Bayesian Multivariate Factor Analysis Model for Evaluating an Intervention by Using Observational Time Series Data on Multiple Outcomes. In Journal of the Royal Statistical Association, Series A, 2020.

Pantelis Samartsidis, Silvia Montagna, Angela R. Laird, Peter T. Fox, Timothy D. Johnson, Thomas E. Nichols. Estimating the Prevalence of Missing Experiments in a Neuroimaging Meta‐analysis. In Research Synthesis Methods, 2020.

Silvia Montagna, James Hopker. A Bayesian Approach for the Use of Athlete Performance Data Within Anti-doping. In Frontiers in Physiology, 2018.

Silvia Montagna, Tor Wager, Lisa Feldman Barrett, Timothy D. Johnson, Thomas E. Nichols. Spatial Bayesian Latent Factor Regression Modeling of Coordinate‐based Meta‐analysis Data. In Biometrics, 2018.

Pantelis Samartsidis, Silvia Montagna, Timothy D. Johnson, Thomas E. Nichols. The Coordinate-based Meta-analysis of Neuroimaging Data. In Statistical Science, 2017.

Silvia Montagna, Surya T. Tokdar. Computer Emulation with Nonstationary Gaussian Processes. In SIAM/ASA Journal on Uncertainty Quantification, 2016.

Silvia Montagna, Surya T. Tokdar, Brian Neelon, David B. Dunson. Bayesian Latent Factor Regression for Functional and Longitudinal Data. In Biometrics, 2012.