A flexible zero-inflated model to address data dispersion
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Publication:86477
DOI10.1016/j.csda.2016.01.007zbMath1468.62176OpenAlexW2277833844MaRDI QIDQ86477
Andrew M. Raim, Kimberly F. Sellers, Andrew M. Raim
Publication date: July 2016
Published in: Computational Statistics & Data Analysis, Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.csda.2016.01.007
Computational methods for problems pertaining to statistics (62-08) Generalized linear models (logistic models) (62J12)
Related Items (21)
Analyzing clustered count data with a cluster-specific random effect zero-inflated Conway–Maxwell–Poisson distribution ⋮ Zero-one inflated negative binomial - beta exponential distribution for count data with many zeros and ones ⋮ A multilevel zero-inflated Conway–Maxwell type negative binomial model for analysing clustered count data ⋮ A flexible regression model for zero- and k-inflated count data ⋮ A mixture model with Poisson and zero-truncated Poisson components to analyze road traffic accidents in Turkey ⋮ Zero inflated Waring distribution ⋮ Type I multivariate zero‐inflated COM–Poisson regression model ⋮ Analyzing longitudinal clustered count data with zero inflation: Marginal modeling using the Conway–Maxwell–Poisson distribution ⋮ A flexible distribution class for count data ⋮ Zero-inflated sum of Conway-Maxwell-Poissons (ZISCMP) regression ⋮ Latent multivariate log-gamma models for high-dimensional multitype responses with application to daily fine particulate matter and mortality counts ⋮ A flexible bivariate distribution for count data expressing data dispersion ⋮ Underdispersion models: Models that are “under the radar” ⋮ Extended Poisson–Tweedie: Properties and regression models for count data ⋮ A Weibull-count approach for handling under- and overdispersed longitudinal/clustered data structures ⋮ On Poisson-exponential-Tweedie models for ultra-overdispersed count data ⋮ Zero-inflated count time series models using Gaussian copula ⋮ COMPoissonReg ⋮ Three-level zero-inflated Conway-Maxwell-Poisson regression model for analyzing dispersed clustered count data with extra zeros ⋮ Unnamed Item ⋮ Copula-based Markov zero-inflated count time series models with application
Uses Software
Cites Work
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