Models for Longitudinal Data with Applications to Early Warning Systems: Workshops of the PRIN Project, Perugia, Italy, 19 September 2024, 11 ... Proceedings in Mathematics & Statistics, 553) - Hardcover

Über die Autorin bzw. den Autor

Francesco Bartolucci is a Full Professor of Statistics at the University of Perugia, fellow of the Institute of Mathematical Statistics, and Editor of Statistical Modelling: An International Journal. His research is in statistics and econometrics, focusing mainly on latent variable models, in particular hidden Markov models, for complex data with applications in different fields, ranging from economics to health.

 Paolo Li Donni is Full Professor of Public Economics at the University of Palermo. His research lies at the intersection of econometrics, public finance, and health economics. It combines applied microeconometrics with structural and Bayesian approaches to study healthcare demand, provider competition, and the organization of hospital and primary-care networks.

 Fulvia Pennoni is Full Professor of Statistics at the University of Milano-Bicocca. Her research focuses on latent variable models, including hidden Markov models, with applications in social sciences, health, and finance. She is the author of numerous international scientific publications and two books in statistical modelling.

 Claudia Pigini is Associate Professor of Econometrics at the Marche Polytechnic University. Her research focuses on panel data models, with applications in several areas of economics, including labor economics, household finance, the economics of innovation, and banking. She is the author of international publications in microeconometrics and applied economics.

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This open access book addresses key methodological and applied issues in rare event forecasting, with a particular focus on early warning systems based on hidden Markov models. It brings together recent advances developed by a cohesive and multidisciplinary group of researchers. A distinctive feature of the volume is its strong emphasis on real-world problems in economics, finance and health, illustrated using empirical datasets.