Marco Bee

According to our database, Marco Bee authored at least 14 papers between 2005 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2023

Unsupervised mixture estimation via approximate maximum likelihood based on the Cramér - von Mises distance.

Marco Bee

Comput. Stat. Data Anal., September, 2023

2022

The truncated g-and-h distribution: estimation and application to loss modeling.

Marco Bee

Comput. Stat., 2022

Estimating the wrapped stable distribution via indirect inference.

Marco Bee

Commun. Stat. Simul. Comput., 2022

2021

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

2018

Likelihood-based risk estimation for variance-gamma models.

Marco Bee, Maria Michela Dickson, Flavio Santi

Stat. Methods Appl., 2018

2017

Density approximations and VaR computation for compound Poisson-lognormal distributions.

Marco Bee

Commun. Stat. Simul. Comput., 2017

Approximate maximum likelihood estimation of the Bingham distribution.

Marco Bee, Roberto Benedetti, Giuseppe Espa

Comput. Stat. Data Anal., 2017

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 autologistic model.

Marco Bee, Giuseppe Espa, Diego Giuliani

Comput. Stat. Data Anal., 2015

2013

A Maximum Entropy Approach to Loss Distribution Analysis.

Marco Bee

Entropy, 2013

On maximum likelihood estimation of a Pareto mixture.

Marco Bee, Roberto Benedetti, Giuseppe Espa

Comput. Stat., 2013

2011

Characteristic function estimation of Ornstein-Uhlenbeck-based stochastic volatility models.

Emanuele Taufer, Nikolai Leonenko, Marco Bee

Comput. Stat. Data Anal., 2011

2009

Importance Sampling for Sums of Lognormal Distributions with Applications to Operational Risk.

Marco Bee

Commun. Stat. Simul. Comput., 2009

2005

Estimating rating transition probabilites with missing data.

Marco Bee

Stat. Methods Appl., 2005