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Research

Dynamic Evaluation of Electoral Preferences in Mexico: A Bayesian Power Ranking Model

Anzarut, M., González, L. F., and Ortiz, M.T. (2024). Selected contributions on Statistics and data science in Latin America. Springer. (In print)

Bayesian Hierarchical Multinomial Modeling of the 2021 Mexican Election Outcomes with Censored Samples

Anzarut, M., González, L. F., and Ortiz, M.T. (2022). Selected contributions on Statistics and data science in Latin America. Springer. 

Estimating COVID-19 cases and reproduction number in Mexico. 

Anzarut, M., González, L. F., Mendizábal, S., and Ortiz, M. T. (2020). arXiv preprint arXiv:2007.09117.

A Heavy-tailed Multilevel Mixture Model for the Quick Count in the Mexican Elections of 2018

Anzarut, M., González, L. F., and Ortiz, M.T. (2019). Selected contributions on Statistics and data science in Latin America. Springer.

A Harris process to model stochastic volatility

Anzarut, M., and Mena, R. H. (2019). Econometrics and Statistics, 10, 151-169.

Poisson Driven Stationary Markov Models.

Anzarut, M., Mena, R., Nava, C. and Prünster, I. (2017). Journal of Business and Economic Statistics.

Construcción y validación de un instrumento para evaluar ambientes clínicos de aprendizaje en las especialidades médicas.

Sutton, A. H., Chacalo, M. A., de la Cruz Flores, G., de la Roche, O. F. R., Montalvo, C. L., & Puig, P. V. (2013).  Gaceta Médica de México, 149(4), 394-405. 

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