SNII Área I PROBABILIDAD 72 MARTIN GONZALEZ, EHYTER MATIAS
MARTIN GONZALEZ, EHYTER MATIAS

MARTIN GONZALEZ, EHYTER MATIAS

MATEMÁTICAS · Nivel 1

insurance risk theory copula theory estimation of tail dependence extreme value theory

Información*

Nombre EHYTER MATIAS MARTIN GONZALEZ
Área FÍSICO-MATEMÁTICAS Y CIENCIAS DE LA TIERRA
Campo MATEMÁTICAS
Disciplina PROBABILIDAD
Especialidad RIESGO
CVU 337161
Institución
Dependencia CAMPUS GUANAJUATO
Entidad GUANAJUATO
Nivel 1
Vigencia Inicio: 01/01/2022
Fin: 31/12/2026

* Información del primer trimestre de 2026.
Fuente: SECIHTI.

Publicaciones ORCID

2026
Stochastic modelling and statistical inference for the time to extinction of a class of populations with sexual reproduction Journal of Mathematical Biology
2025
How Fast Does Extinction Occur in Bisexual Populations With Size-Dependent Mating Dynamics? Methodology and Computing in Applied Probability
2024
A note on series representation for the q-scale function of a class of spectrally negative Lévy processes Statistics & Probability Letters
2023
Expected discounted penalty function and asymptotic dependence of the severity of ruin and surplus prior to ruin for two-sided Lévy risk processes Communications in Statistics - Theory and Methods
A new definition of hitting time and an embedded Markov chain in continuous-time quantum walks Quantum Information Processing
2022
Gerber-Shiu Function for a Class of Markov-Modulated Lévy Risk Processes with Two-Sided Jumps Methodology and Computing in Applied Probability
Mathematical modelling of student’s cumulative learning Nova Scientia
2021
Approximation of the Equilibrium Distribution via Extreme Value Theory: an Application to Insurance Risk Methodology and Computing in Applied Probability
2019
The distribution and asympotic behaviour of the negative Wiener–Hopf factor for Lévy processes with rational positive jumps Journal of Applied Probability
2018
Asymptotic Results for the Severity and Surplus Before Ruin for a Class of Lévy Insurance Processes XII Symposium of Probability and Stochastic Processes