Discrete Data Time Series Models

• Grant number: 19/21766-8
• Support Opportunities: Scholarships abroad - Research
• Start date: February 02, 2020
• End date: February 01, 2021
• Field of knowledge: Physical Sciences and Mathematics - Probability and Statistics - Applied Probability and Statistics
• Principal Investigator: Marinho Gomes de Andrade Filho
• Grantee: Marinho Gomes de Andrade Filho
• Host Investigator: Nalini Ravishanker
• Host Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
• Institution abroad: University of Connecticut (UCONN), United States
• Associated research grant: 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry., AP.CEPID

Abstract

This project aims to develop Zero-Modified (e.g. Inflated or Zero Deflated) models for time series with discrete data. The models developed in this project originate from some of the Zero-Modified models of the Power Series family (Poisson, Generalized Poisson, Binomial, Negative Binomial, COM-Poisson among others). In this work these models will be defined in the context of time series to accommodate time correlated count data with excess (or deficit) zeros. Inference methods based on the classical likelihood approach andthe Bayesian approach together with Markov Chain Monte Carlo techniques will be considered. The project also provides relevant applications on real problems.

Scientific publications

(9)

(The scientific publications listed on this page originate from the Web of Science or SciELO databases. Their authors have cited FAPESP grant or fellowship project numbers awarded to Principal Investigators or Fellowship Recipients, whether or not they are among the authors. This information is collected automatically and retrieved directly from those bibliometric databases.)

BERTOLI, WESLEY; CONCEICAO, KATIANE S.; ANDRADE, MARINHO G.; LOUZADA, FRANCISCO. A New Regression Model for the Analysis of Overdispersed and Zero-Modified Count Data. Entropy, v. 23, n. 6, JUN 2021. (13/07375-0, 19/21766-8, 19/22412-5)

ANDRADE, MARINHO G.; CONCEICAO, KATIANE S.; RAVISHANKER, NALINI. Zero-modified count time series modeling with an application to influenza cases. AStA-Advances in Statistical Analysis, v. 108, n. 3, p. 27-pg., 2023-11-27. (19/22412-5, 19/21766-8)

CONCEICAO, KATIANE S.; ANDRADE, MARINHO G.; LACHOS, VICTOR HUGO; RAVISHANKER, NALINI. Bayesian Inference for Zero-Modified Power Series Regression Models. MATHEMATICS, v. 13, n. 1, p. 30-pg., 2025-01-01. (19/22412-5, 19/21766-8)

BERTOLI, WESLEY; CONCEICAO, KATIANE S.; ANDRADE, MARINHO G.; LOUZADA, FRANCISCO. A new mixed-effects regression model for the analysis of zero-modified hierarchical count data. BIOMETRICAL JOURNAL, v. 63, n. 1, p. 24-pg., 2020-10-19. (19/22412-5, 19/21766-8)

RAQUEL, GABRIELA C.; CONCEICAO, KATIANE S.; PRATES, MARCOS O.; ANDRADE, MARINHO G.. A zero-modified Poisson mixed model with generalized random effect. JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, MAR 2021. (19/22412-5, 19/21766-8)

CONCEICAO, KATIANE S.; SUZUKI, ADRIANO K.; ANDRADE, MARINHO G.. A Bayesian approach for zero-modified Skellam model with Hamiltonian MCMC. Statistical Methods and Applications, JUL 2020. (19/21766-8, 19/22412-5)

SANTANA, ROGERIO A.; CONCEICAO, KATIANE S.; DINIZ, CARLOS A. R.; ANDRADE, MARINHO G.. ype I multivariate zero-inflated COM-Poisson regression mode. BIOMETRICAL JOURNAL, NOV 2021. (19/22412-5, 19/21766-8)

RAQUEL, GABRIELA C.; CONCEICAO, KATIANE S.; PRATES, MARCOS O.; ANDRADE, MARINHO G.. A zero-modified Poisson mixed model with generalized random effect. JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, v. 91, n. 12, p. 18-pg., 2021-03-10. (19/22412-5, 19/21766-8)

CONCEICAO, KATIANE S.; SUZUKI, ADRIANO K.; ANDRADE, MARINHO G.. A Bayesian approach for zero-modified Skellam model with Hamiltonian MCMC. Statistical Methods and Applications, v. 30, n. 2, p. 19-pg., 2020-07-18. (19/22412-5, 19/21766-8)