Adjusted residuals in zero-inflated regression models

• Grant number: 13/17876-6
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Start date: January 01, 2014
• End date: March 31, 2014
• Field of knowledge: Physical Sciences and Mathematics - Probability and Statistics - Statistics
• Principal Investigator: Denise Aparecida Botter
• Grantee: Gustavo Henrique de Araujo Pereira
• Host Institution: Instituto de Matemática e Estatística (IME). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• Associated research grant: 12/21788-2 - Regression models and applications, AP.TEM

Abstract

Zero-inflated regression models are used to fit response variables that assume the zero value more frequently than expected bya known probability distribution. In this work, we focus on response variables whose distribution is a mixture of a continuous distribution and a degenerate distribution that assigns non-negative probability to zero. The aim of this work is to obtain adjusted residuals to perform diagnostic analysis in this class of zero-inflated regression models using, for instance, the methodology presented by Cox and Snell (1968). The properties of the adjusted residuals will be studied using Monte Carlo simulation and applications to real data will be performed.

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)

PEREIRA, GUSTAVO H. A.; SCUDILIO, JULIANA; SANTOS-NETO, MANOEL; BOTTER, DENISE A.; SANDOVAL, MONICA C.. A class of residuals for outlier identification in zero adjusted regression models. Journal of Applied Statistics, NOV 2019. (13/17876-6)

PEREIRA, GUSTAVO H. A.; SCUDILIO, JULIANA; SANTOS-NETO, MANOEL; BOTTER, DENISE A.; SANDOVAL, MONICA C.. A class of residuals for outlier identification in zero adjusted regression models. Journal of Applied Statistics, v. 47, n. 10, p. 15-pg., 2019-11-30. (13/17876-6)