Investigación/Research

  • Publicados
  1. Baltazar-Larios, F., Delgado-Vences, F. and Diaz-Infante, S., 2022. Maximum likelihood estimation for a stochastic SEIR system for COVID-19. International Journal of Computer Mathematics. https://doi.org/10.1080/00207160.2022.2148316
  2. Baltazar-Larios, F.and Esparza, Luz Judith R., 2022. Statistical inference for partially observed Markov-Modulated Diffusion Risk Model. Methodology and Computing in Applied Probability. https://doi.org/10.1007/s11009-022-09932-7
  3. Martínez J. and Baltazar-Larios, F., 2022. Approximations of the Ultimate Ruin Probability in the classical risk model using the Banach’s Fixed-Point Theorem and the Continuity of the Ruin Probability. Kybernetika. http://doi.org/10.14736/kyb-2022-2-0254
  4. Delgado-Vences, F., Baltazar-Larios, F., Ornelas A., Morales-Bojórquez, E., Cruz- Escalona, V.H. and Salomón Aguilar, C, 2022. Inference for a discretized stochastic logistic differential equation and its application to biological growth. Journal of Applied Statistics. https://doi.org/10.1080/02664763.2021.2024154
  5. Reynoso, B., Baltazar-Larios, F., Eslava, L., 2022. Maximum Likelihood Estimation for a Markov-Modulated Jump-Diffusion Model. Interdisciplinary Statistics in Mexico. https://doi.org/10.1007/978-3-031-127786 11
  6. Esparza, Luz Judith R. and Baltazar-Larios, F., 2022. Bayesian Estimation for a Mortality Model via the Aging Process. Statistics and Its Interface. https://dx.doi.org/10.4310/21-SII670
  7. Baltazar-Larios, F. and Esparza, Luz Judith R., 2021. Modelación de la Mortalidad en México 2000-2015 utilizando Distribuciones Tipo Fase. INTERDISCIPLINA, UNAM.  https://doi.org/10.22201/ceiich.24485705e.2021.25.79978
  8. Baltazar-Larios, F. and Esparza, Luz Judith R., 2019. Bayesian estimation for the Markov-Modulated Diffusion Risk Model. Springer Proceedings in Mathematics & Sta- tistics.  https://doi.org/10.1007/978-3-030-31551-1 2
  9. Baltazar-Larios, F. and Esparza, Luz Judith R., 2017. A Stochastic EM algorithm for construction of Mortality Tables. Annals Actuarial Science.   https://doi.org/10.1017/S1748499517000094
  10. Baltazar-Larios, F. y Cano Vaca O., 2015. Estimación de la mortalidad vía distribuciones tipo fase. Proceedings of the Second International Conference on Mathematics and its Applications.  https://www.fcfm.buap.mx/cima/public/docs/publicaciones/ memorias2cima.pdf
  11. Baltazar-Larios, F., 2014. Estimación de paleotemperaturas vía procesos de difusión integrados. Miscelanea Matemática.  https://miscelaneamatematica.org/download/tbl articulos.pdf2.9552b38928dd0113.35383130362e706466. pdf
  12. Baltazar-Larios, F. and Padilla, P., 2012 A minimum-entropy-production criterion to com- pare credit risk models. Numerical Analysis and Applied Mathematics ICNAAM.  https://doi.org/10.1063/1.4756572
  13. Baltazar-Larios, F. and Sørensen, M., 2010. Maximum likelihood estimation for integrated diffusion processes. Contemporary Quantitative Finance. https://doi.org/10.1007/978-3-642-03479-4 20
  • Sometidos
  1.  Baltazar-Larios, F., Delgado-Vences, F. and Ornelas A. Parameter estimation and model selection for stochastic differential equations for biological growth. https://doi. org/10.48550/arXiv.2301.08294
  2. Baltazar-Larios, F., and Delgado-Vences, F. Animal movement dispersion with stochastic partial differential equations: Inference and simulations. https://doi.org/10.48550/ arXiv.2301.08301
  3.  Baltazar-Larios, F. and R. Esparza, Luz Judith. A novel method and comparison of methods for constructing Markov bridges. https://arxiv.org/abs/2301.06098