Leptokurtic and platykurtic class of robust symmetrical and asymmetrical time series models

DOI10.1016/j.cam.2020.112806zbMath1436.62422OpenAlexW3013756208MaRDI QIDQ1987420

Safdar Ghasami, Mohsen Maleki, Zahra Khodadadi

Publication date: 15 April 2020

Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cam.2020.112806

zbMATH Keywords

maximum likelihood estimatesautoregressive modeltwo-piece distributionsECME-algorithmscale mixtures of normal family

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Related Items (6)

Modeling and forecasting the spread and death rate of coronavirus (COVID-19) in the world using time series models ⋮ A Bayesian approach on the two-piece scale mixtures of normal homoscedastic nonlinear regression models ⋮ 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 ⋮ Application of state-space model with skew-\(t\) measurement noise to blood test value prediction ⋮ Heteroscedastic nonlinear regression models using asymmetric and heavy tailed two-piece distributions

Uses Software

• R

Cites Work

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