Symmetrical and asymmetrical mixture autoregressive processes

DOI10.1214/19-BJPS429zbMath1445.62233OpenAlexW3022291642MaRDI QIDQ783302

Reinaldo B. Arellano-Valle, Mohsen Maleki, Arezo Hajrajabi

Publication date: 12 August 2020

Published in: Brazilian Journal of Probability and Statistics (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.bjps/1588579221

zbMATH Keywords

nonlinear time seriesscale mixtures of skew-normal distributionsECME-algorithm (expectation/conditional maximisation either)finite mixtures of autoregressive models

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Related Items (4)

Robust clustering of COVID-19 cases across U.S. counties using mixtures of asymmetric time series models with time varying and freely indexed covariates ⋮ Robust mixture regression modeling based on two-piece scale mixtures of normal distributions ⋮ Heteroscedastic nonlinear regression models using asymmetric and heavy tailed two-piece distributions ⋮ Nonlinear autoregressive stochastic frontier model with dynamic technical inefficiency in panel data

Uses Software

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