Spatiotemporal Models for Sequential Data from Multiple Sources through Markov Chains of Variable Length incorporating Exogenous Covariates

• Grant number: 24/13099-0
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date: December 01, 2024
• End date: February 29, 2028
• Field of knowledge: Physical Sciences and Mathematics - Probability and Statistics - Applied Probability and Statistics
• Principal Investigator: Nancy Lopes Garcia
• Grantee: Marília Gabriela Rocha
• Host Institution: Instituto de Matemática, Estatística e Computação Científica (IMECC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Associated research grant: 23/13453-5 - Stochastic systems modeling, AP.TEM

Abstract

Variable Length Markov Chains have been used in many fields for temporal stochastic processes in finite state space. Recently, exogenous information has been incorporated into these models in order to better predict the transition probability. On the other hand, when several sources are used, it is not yet known how to incorporate the spatial dependence between the chains.