Heteroscedastic nonlinear regression models using asymmetric and heavy tailed two-piece distributions

DOI10.1007/s10182-020-00384-3zbMath1480.62139OpenAlexW3097832718MaRDI QIDQ2058551

Zahra Khodadadi, Akram Hoseinzadeh, Mohsen Maleki

Publication date: 9 December 2021

Published in: AStA. Advances in Statistical Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10182-020-00384-3

zbMATH Keywords

ECME algorithmheteroscedastic nonlinear regression modeltwo-piece scale mixtures of normal distributions

Mathematics Subject Classification ID

Statistics of extreme values; tail inference (62G32) General nonlinear regression (62J02)

Related Items (4)

A Bayesian approach on the two-piece scale mixtures of normal homoscedastic nonlinear regression models ⋮ SKEWED AUTO-REGRESSIVE PROCESS WITH EXOGENOUS INPUT VARIABLES: AN APPLICATION IN THE ADMINISTERED VACCINE DOSES ON COVID-19 SPREAD ⋮ 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

Uses Software

• R
• JAGS
• Stan

Cites Work

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