Covariate enabled variable length Markov Chains

• Grant number: 19/04535-2
• Support Opportunities: Research Grants - Visiting Researcher Grant - International
• Start date: August 01, 2019
• End date: August 21, 2019
• Field of knowledge: Physical Sciences and Mathematics - Probability and Statistics - Applied Probability and Statistics
• Principal Investigator: Nancy Lopes Garcia
• Grantee: Nancy Lopes Garcia
• Visiting researcher: Adriano Zanin Zambom
• Visiting researcher institution: California State University, Northridge, United States
• Host Institution: Instituto de Matemática, Estatística e Computação Científica (IMECC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Associated research grant: 17/10555-0 - Stochastic modeling of interacting systems, AP.TEM

Abstract

Markov Chains with variable length have been widely explored in the literature of probability andstatistics. However, little is known when the transition probabilities depend on exogenous variables. Wepropose novel context algorithms and search for the conditions and asymptotic behavior of the estimatedcontext trees. (AU)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

ZAMBOM, ADRIANO ZANIN; ALFONSO COLLAZOS, JULIAN; DIAS, RONALDO. Selection of the number of clusters in functional data analysis. JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, v. 92, n. 14, p. 19-pg., 2022-03-23. (19/04535-2, 17/15306-9, 18/04654-9)