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Zero‐inflated modeling part II: Zero‐inflated models for complex data structures

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Abstract The prequel to this review provided an extensive treatment of classic zero‐inflated count regression models where a univariate discrete distribution is used for the count regression component of the model. The treatment of zero inflation beyond the classic univariate count regression setting has seen a substantial increase in recent years. This second review paper surveys some of this recent literature and focuses on important developments in handling zero inflation for correlated count settings, discrete time series models, spatial models, and multivariate models. We discuss some of the available computational tools for performing estimation in these settings, while again highlighting the diverse data problems that have been addressed using these methods. This article is categorized under: Statistical Models > Multivariate Models Statistical Models > Generalized Linear Models Statistical and Graphical Methods of Data Analysis > Bayesian Methods and Theory
Coefficient estimates and confidence intervals for the fixed effects from the eight model fits to the owl nestlings data
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Estimated random effects for the 27 nest sites for the ZIGP regression fit. The red horizontal line is the average of these 27 random nest location effects, which is at 0.012
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Statistical and Graphical Methods of Data Analysis > Bayesian Methods and Theory
Statistical Models > Generalized Linear Models
Statistical Models > Multivariate Models

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