Selected Contributions on Statistics and Data Science in Latin America

1. Front Matter

   Pages i-viii

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2. A Heavy-Tailed Multilevel Mixture Model for the Quick Count in the Mexican Elections of 2018

   • Michelle Anzarut, Luis Felipe González, María Teresa Ortiz

   Pages 1-13

3. Bayesian Estimation for the Markov-Modulated Diffusion Risk Model

   • F. Baltazar-Larios, Luz Judith R. Esparza

   Pages 15-31

4. Meta-Analysis in DTA with Hierarchical Models Bivariate and HSROC: Simulation Study

   • Sergio A. Bauz-Olvera, Johny J. Pambabay-Calero, Ana B. Nieto-Librero, Ma. Purificación Galindo-Villardón

   Pages 33-42

5. Compound Dirichlet Processes

   • Arrigo Coen, Beatriz Godínez-Chaparro

   Pages 43-58

6. An Efficient Method to Determine the Degree of Overlap of Two Multivariate Distributions

   • Eduardo Gutiérrez-Peña, Stephen G. Walker

   Pages 59-68

7. Clustering via Nonsymmetric Partition Distributions

   • Asael Fabian Martínez

   Pages 69-80

8. A Flexible Replication-Based Classification Approach for Parkinson’s Disease Detection by Using Voice Recordings

   • Lizbeth Naranjo, Ruth Fuentes-García, Carlos J. Pérez

   Pages 81-94

9. Calibration of Population Growth Mathematical Models by Using Time Series

   • Francisco Novoa-Muñoz, Sergio Contreras Espinoza, Aníbal Coronel Pérez, Ian Hess Duque

   Pages 95-110

10. Impact of the Red Code Process Using Structural Equation Models

    • Eduardo Pérez Castro, Flaviano Godínez Jaimes, Elia Barrera Rodríguez, Ramón Reyes Carreto, Raúl López Roque, Virginia Vera Leyva

    Pages 111-125

11. On a Construction of Stationary Processes via Bilateral Matrix-Exponential Distributions

    • Luz Judith R. Esparza

    Pages 127-143

12. BoostNet: Bootstrapping Detection of Socialbots, and a Case Study from Guatemala

    • E. I. Velazquez Richards, E. Gallagher, P. Suárez-Serrato

    Pages 145-154

The volume includes a collection of peer-reviewed contributions from among those presented at the main conference organized yearly by the Mexican Statistical Association (AME) and every two years by a Latin-American Confederation of Statistical Societies. For the 2018 edition, particular attention was placed on the analysis of highly complex or large data sets, which have come to be known as “big data”. Statistical research in Latin America is prolific and research networks span within and outside the region. The goal of this volume is to provide access to selected works from Latin-American collaborators and their research networks to a wider audience. New methodological advances, motivated in part by the challenges of a data-driven world and the Latin American context, will be of interest to academics and practitioners around the world. 

• Bayesian Computing
• Bayesian Inference for Big Data
• Bayesian Nonparametric Methods
• Computational Methods for Bayesian Inference
• Environmental Statistics
• Spatial Statistics
• Variational Bayesian Inference

• Department of Environmental Sciences, Informatics and Statistics, Ca' Foscari University of Venice, Venice, Italy

  Isadora Antoniano-Villalobos

• Department of Probability and Statistics, IIMAS, UNAM, Mexico City, Mexico

  Ramsés H. Mena

• Department of Statistics, Instituto Tecnológico Autónomo de México, Mexico City, Mexico

  Manuel Mendoza, Luis E. Nieto-Barajas

• Department of Mathematics, Facultad de Ciencias, UNAM, Mexico City, Mexico

  Lizbeth Naranjo

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