Estimating rating transition probabilites with missing data. - Marco Bee (Stat. Methods Appl., 2005)

Importance Sampling for Sums of Lognormal Distributions with Applications to Operational Risk. - Marco Bee (Commun. Stat. Simul. Comput., 2009)

Characteristic function estimation of Ornstein-Uhlenbeck-based stochastic volatility models. - Emanuele Taufer; Nikolai Leonenko; Marco Bee (Comput. Stat. Data Anal., 2011)

On maximum likelihood estimation of a Pareto mixture. - Marco Bee; Roberto Benedetti; Giuseppe Espa (Comput. Stat., 2013)

A Maximum Entropy Approach to Loss Distribution Analysis. - Marco Bee (Entropy, 2013)

Approximate maximum likelihood estimation of the autologistic model. - Marco Bee; Giuseppe Espa; Diego Giuliani (Comput. Stat. Data Anal., 2015)

Estimation of the Lognormal-Pareto Distribution Using Probability Weighted Moments and Maximum Likelihood. - Marco Bee (Commun. Stat. Simul. Comput., 2015)

Approximate maximum likelihood estimation of the Bingham distribution. - Marco Bee; Roberto Benedetti; Giuseppe Espa (Comput. Stat. Data Anal., 2017)

Density approximations and VaR computation for compound Poisson-lognormal distributions. - Marco Bee (Commun. Stat. Simul. Comput., 2017)

Likelihood-based risk estimation for variance-gamma models. - Marco Bee; Maria Michela Dickson; Flavio Santi (Stat. Methods Appl., 2018)

Testing a parameter restriction on the boundary for the g-and-h distribution: a simulated approach. - Marco Bee; Julien Hambuckers; Flavio Santi; Luca Trapin (Comput. Stat., 2021)

Estimating the wrapped stable distribution via indirect inference. - Marco Bee (Commun. Stat. Simul. Comput., 2022)

The truncated g-and-h distribution: estimation and application to loss modeling. - Marco Bee (Comput. Stat., 2022)

Unsupervised mixture estimation via approximate maximum likelihood based on the Cramér - von Mises distance. - Marco Bee (Comput. Stat. Data Anal., 2023)

On discriminating between lognormal and Pareto tail: an unsupervised mixture-based approach. - Marco Bee (Adv. Data Anal. Classif., 2024)

A parsimonious dynamic mixture for heavy-tailed distributions. - Marco Bee (Math. Comput. Simul., 2025)