Litcius/Paper detail

<scp>Zero‐inflated</scp>modeling part<scp>II</scp>:<scp>Zero‐inflated</scp>models for complex data structures

Derek S. Young, Eric S. Roemmele, Xuan Shi

2020Wiley Interdisciplinary Reviews Computational Statistics10 citationsDOI

Abstract

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 &gt; Multivariate Models Statistical Models &gt; Generalized Linear Models Statistical and Graphical Methods of Data Analysis &gt; Bayesian Methods and Theory

Topics & Concepts

Count dataUnivariateMultivariate statisticsGeneralized linear modelBayesian probabilityZero (linguistics)StatisticsComputer scienceStatistical modelEconometricsInflation (cosmology)MathematicsPoisson distributionTheoretical physicsLinguisticsPhilosophyPhysicsStatistical Methods and Bayesian InferenceBayesian Methods and Mixture ModelsStatistical Methods and Inference