PENNONI FULVIA

Role
Full Professor  
Academic disciplines
Statistics (STAT-01/A)
Scientific-Disciplinary Group:
STATISTICS (13/STAT-01)
Email
[email protected]
Office phone
0264485856
Room:
  • U07, Floor: 2, Room: 2058
Reception hours

 

 

Biography

Fulvia Pennoni is Full Professor of Statistics at the Department of Statistics and Quantitative Methods of the University of Milano-Bicocca. She holds a Ph.D. in Statistics from University of Florence (Italy, 2004) and a Degree in Economics and Business Administration from University of Perugia (Italy, 2000). She has been a researcher at the Joint Research Centre (Institute for Protection of the Citizens, Unit of Applied Statistics and Econometrics) of the European Commission since 2006. She published books and research articles in international disciplinary journals on composite indicators, graphical models, latent variable models, and models for the analysis of longitudinal data. 

Publications

  • Pennoni, F. (2024). Maximum Likelihood Estimation of Multivariate Regime Switching Student-t Copula Models. Intervento presentato a: 2nd International Conference on Computational Finance and Business Analytics CFBA, Interscience Institute of Management and Technology, Odisha, India. Detail

  • Pennoni, F. (2024). Latent probability models for cross-sectional and longitudinal data. In Latent variable models: methodological and applicative developments for lifestyle and society. 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

  • 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

Full list

Research projects

Hidden Markov Models for Early Warning Systems
Year: 2022
Call: FAQC 2022 - seconda finestra
Grantors: Università degli Studi di MILANO-BICOCCA
PNRR per la Missione 4, componente 2 Investimento 1.1- Avviso 104/2022 | Hidden Markov Models for Early Warning Systems
Year: 2022
Call: Bando PRIN 2022
Grantors: MINISTERO DELL'UNIVERSITA' E DELLA RICERCA (MUR)
“InPreSa: Individuazione Precoce e contenimento SARS‐siCoV‐2. Strumenti e servizi per affrontare la sfida al Covid19.”
Year: 2020
Call: Misura a sostegno dello sviluppo di collaborazioni per l'identificazione di terapia e sistemi di diagnostica, protezione e analisi per contrastare l'emergenza Coronavirus e altre emergenze virali del futuro - Linea 2
Grantors: REGIONE LOMBARDIA
Modelli mistura e a variabili latenti per l'inferenza causale e l'analisi di dati socio-economici
Year: 2013
Call: 2011-117 - Firb - Futuro in Ricerca 2012
Grantors: M.I.U.R. - MINISTERO DELL'ISTRUZIONE, DELL'UNIVERSITA' E DELLA RICERCA

Awards

Research and teaching assignments

  • Attivita' di insegnamento - Teaching mobility (Call 2015 KA1, Erasmus+ programme) Department of Management/Economics and Financial Analysis. Teaching on Multivariate Data Analysis with R - Uniwersytet Ekonomiczny w Katowicach, 2016

Further links