Modelling nonlinear count time series with local mixtures of Poisson autoregressions

DOI10.1016/j.csda.2006.09.032zbMath1445.62223OpenAlexW2011696639MaRDI QIDQ1020204

Martin A. Tanner, Alexandre X. Carvalho

Publication date: 29 May 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2006.09.032

zbMATH Keywords

maximum likelihood estimationcount dataPoisson regressionnonlinear time seriesmixtures-of-experts

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items (8)

Hierarchical mixture-of-experts models for count variables with excessive zeros ⋮ Modeling nonlinearities with mixtures-of-experts of time series models ⋮ On Estimation of the Bivariate Poisson INAR Process ⋮ Autoregressive models with mixture of scale mixtures of Gaussian innovations ⋮ Time Series Mixtures of GeneralizedtExperts: ML Estimation and an Application to Stock Return Density Forecasting ⋮ Editorial: Advances in mixture models ⋮ On Convergence Rates of Mixtures of Polynomial Experts ⋮ Mixtures of Nonlinear Poisson Autoregressions

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