Multiple modification points in discrete data models

• Grant number: 19/22412-5
• 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 - Statistics
• Principal Investigator: Katiane Silva Conceição
• Grantee: Katiane Silva Conceição
• 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

Abstract

Count datasets are common in many areas of knowledge and, consequently, more general discrete distributions have been proposed due to the unique characteristics of each set. In particular, count data may present discrepancies (greater or lesser) in the observed frequencies of two observations, said k1 and k2, by comparing them with their expected frequencies obtained from a particular discrete distribution. In this sense, a modification in the probability mass function of discrete distributions is essential to adequately explain the behavior of the data. Following this context, the main objective of this project is to propose the family of discrete distributions k1 and k2 modified, which are able to model data sets that present or not some kind of modification (inflation and/or deflation) in the frequency of observations k1 and k2. (AU)

Scientific publications

(9)

(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)

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)

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)

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)

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)