Autoregressive conditional negative binomial model applied to over-dispersed time series of counts

DOI10.1016/J.STAMET.2016.02.001zbMath1487.62106OpenAlexW2279922475MaRDI QIDQ670111

Songsak Sriboonchitta, Cathy W. S. Chen, Mike K. P. So, Jessica C. Li

Publication date: 18 March 2019

Published in: Statistical Methodology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.stamet.2016.02.001

zbMATH Keywords

MCMCnegative binomialPoisson autoregressive modelover-dispersioninteger-valued time series

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items (7)

Copula directional dependence of discrete time series marginals ⋮ Forecasting transaction counts with integer-valued GARCH models ⋮ Forecasting overdispersed INAR(1) count time series with negative binomial marginal ⋮ Hysteretic Poisson INGARCH model for integer-valued time series ⋮ Bayesian inference of nonlinear hysteretic integer-valued GARCH models for disease counts ⋮ Adaptive log-linear zero-inflated generalized Poisson autoregressive model with applications to crime counts ⋮ Bayesian modelling of nonlinear negative binomial integer-valued GARCHX models

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