Mid-quantile mixed graphical models with an application to mass public shootings in the U.S..

Luca Merlo, Marco Geraci, and Lea Petrella

Journal of the Royal Statistical Society Series A: Statistics in Society, (2025).

Quantile and expectile copula-based hidden Markov regression models for the analysis of the cryptocurrency market.

Foroni, Beatrice, Luca Merlo, and Lea Petrella

Statistical Modelling, (2024): 1–19.

Inter-order relations between equivalence for Lp-quantiles of the Student's t distribution

Bignozzi, Valeria, Luca Merlo, and Lea Petrella

Insurance: Mathematics and Economics, 115 (2024): 44-50.

Expectile hidden Markov regression models for analyzing cryptocurrency returns.

Foroni, Beatrice, Luca Merlo, and Lea Petrella

Statistics and Computing, 34.2 (2024): 66.

Unified Unconditional Regression for Multivariate Quantiles, M-Quantiles, and Expectiles.

Merlo, Luca, Petrella, Lea, Salvati, Nicola, and Tzavidis, Nikos

Journal of the American Statistical Association (2023): 1-12.

M-quantile regression shrinkage and selection via the Lasso and Elastic Net to assess the effect of meteorology and traffic on air quality.

Ranalli, M. Giovanna, Salvati, Nicola, Petrella, Lea, and Pantalone, Francesco

Biometrical Journal (2023): 2100355.

Two-part quantile regression models for semi-continuous longitudinal data: a finite mixture approach.

Merlo, Luca, Antonello Maruotti, and Lea Petrella

Statistical Modelling 22.6 (2022): 485-508.

Quantile Regression Forest for Value-at-Risk Forecasting Via Mixed-Frequency Data.

Andreani, Mila, Vincenzo Candila, and Lea Petrella

Methods and Applications in Fluorescence. Cham: Springer International Publishing, 2022. 13-18.


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