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Ricciotti, L., Pollice, A., Paradinas, J., Martino, S. (2026). Spatio-Temporal Variability in Mediterranean Sardine Abundance: A Bayesian Approach. Stochastic Environmental Research and Risk Assessment. Under Review.
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Ricciotti, L., Mahmoud Mohmed Borghol, R., Porcu, M., Maruotti, A. (2026). Modelling Short- and Long-term Flooding Levels in the Venice Lagoon: a Hierarchical Hidden Markov Model Approach. Ecological Indicators. Under review.
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Calculli, C., Ricciotti L., Pollice A. (2026). Bayesian Spatial modelling of Satellite-Derived Wildfire Counts Across Italian Municipalities. Environmental and Ecological Statistics. Under review.
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Ricciotti, L., Russo, A., Holleland, S., Maruotti, A. (2025). Robust regularized conditional heteroscedastic hidden semi-Markov models for the analysis of sea levels in the Venice lagoon. Environmental and Ecological Statistics. Accepted.
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Ricciotti, L., Pollice, A., Picone, M., Martino, S. (2025). Cost-to-coast: space-time modeling of coast defense funds and environmental drivers in Italy. Environmental and Ecological Statistics. https://doi.org/10.1007/s10651-025-00686-2
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Ricciotti, L., & Pollice, A. (2025). Italian investments for soil defence: retrieving and visualizing data by the PublicWorksFinanceIT R Package. Annals of Operations Research, 1-28. https://doi.org/10.1007/s10479-025-06472-4
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Ricciotti, L., Picone, M., Pollice, A., Maruotti, A. (2025). A zero-inflated hidden semi-Markov model with covariate-dependent sojourn parameters for analysing marine data in the Venice lagoon, Journal of the Royal Statistical Society Series C: Applied Statistics, Volume 74, Issue 2, March 2025, Pages 506-529, https://doi.org/10.1093/jrsssc/qlae065
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Maruotti, A., Ricciotti, L., Russo, A. (2025). Multivariate longitudinal latent Markov models to characterize pollutant exposures. Book: Environmental Statistics: Innovative Methods and Applications. Eds: Andriette Bekker, Johan Ferreira, Priyanka Nagar. To Appear.
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Ricciotti, L., & Pollice, A. (2024). An integrated georeferenced dataset of public investments for soil defence in Italy. Data in Brief, 57, 110909. https://doi.org/10.1016/j.dib.2024.110909
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Ricciotti, L., Picone, M., Pollice, A., Maruotti, A (2024). Modelling and Clustering Sea Conditions: Bivariate FiniteMixtures of Generalized Additive Models for Location, Shape, and Scale Applied to the Analysis of Meteorological Tides and Wave Heights. Journal of Marine Science and Engineering. 2024; 12(5):740. https://doi.org/10.3390/jmse12050740
