Mean-shift outliers model in skew scale-mixtures of normal distributions

DOI10.1080/00949655.2015.1110819OpenAlexW2294672124MaRDI QIDQ5222484

Thalita B. Mattos, Clécio S. Ferreira, Narayanaswamy Balakrishnan

Publication date: 1 April 2020

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2015.1110819

zbMATH Keywords

outliersEM algorithmmean-shift modelskew scale-mixtures of normal distributions

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Linear regression; mixed models (62J05) Parametric hypothesis testing (62F03) Point estimation (62F10)

Uses Software

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Cites Work

• Skew scale mixtures of normal distributions: properties and estimation
• The mean-shift outlier model in general weighted regression and its applications.
• On statistical models for regression diagnostics
• Multiple outlier detection in growth curve model with unstructured covariance matrix
• Outlier Detection Using Nonconvex Penalized Regression
• Maximum likelihood estimation via the ECM algorithm: A general framework
• Rejection of Outliers
• Comparing probabilistic methods for outlier detection in linear models
• The ECME algorithm: A simple extension of EM and ECM with faster monotone convergence
• Distributions Generated by Perturbation of Symmetry with Emphasis on a Multivariate Skewt-Distribution
• Influence Diagnostics and Outlier Tests for Semiparametric Mixed Models
• Inference and diagnostics in skew scale mixtures of normal regression models
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