BRUSA LUCA

Brusa, L., Bartolucci, F., Pennoni, F., Peruilh Bagolini, R. (2024). A penalized maximum likelihood estimation for hidden Markov models to address latent state separation. In PROGRAMME AND ABSTRACTS: 26th International Conference on Computational Statistics (COMPSTAT 2024) (pp.29-29). Detail

Brusa, L., Pennoni, F., Bartolucci, F., Peruilh Bagolini, F. (2024). In-sample and out-of-sample forecasts for early warning systems using a hidden Markov model with covariates. Intervento presentato a: 1st Workshop for the PRIN Project "Hidden Markov Models for Early Warning Systems" - ID: 2022-NAZ-0371, Perugia, Italy. Detail

Brusa, L., Matias, C. (2024). Model‐based clustering in simple hypergraphs through a stochastic blockmodel. SCANDINAVIAN JOURNAL OF STATISTICS [10.1111/sjos.12754]. Detail

Brusa, L., Pennoni, F., Bartolucci, F. (2024). Maximum likelihood for discrete latent variable models via evolutionary algorithms. STATISTICS AND COMPUTING, 34(2 (April 2024)), 1-15 [10.1007/s11222-023-10358-5]. Detail

Brusa, L., Pennoni, F., Bartolucci, F., Peruilh Bagolini, R. (2024). Addressing latent state separation in hidden Markov models for categorical data with covariates: A penalised maximum likelihood approach. Intervento presentato a: Challenges for Categorical Data Analysis (CCDA 2024), Londra, United Kingdom. Detail