Bias from misspecification of the component variances in a normal mixture

DOI10.1016/j.csda.2011.04.007zbMath1464.62123OpenAlexW1974883941MaRDI QIDQ1658327

Yungtai Lo

Publication date: 14 August 2018

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

Full work available at URL: https://doi.org/10.1016/j.csda.2011.04.007

zbMATH Keywords

bootstrapEM algorithmasymptotic biasnormal mixturesystolic blood pressure

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Point estimation (62F10)

Related Items (2)

Editorial: The 2nd special issue on advances in mixture models ⋮ Estimating the prevalence of low-lumbar spine bone mineral density in older men with or at risk for HIV infection using normal mixture models

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Medical applications of finite mixture models
• A constrained formulation of maximum-likelihood estimation for normal mixture distributions
• Likelihood ratio tests of the number of components in a normal mixture with unequal variances
• Testing the number of components in a normal mixture
• Consistency of the Maximum Likelihood Estimator in the Presence of Infinitely Many Incidental Parameters
• The Theory of Parametric Identification
• On Information and Sufficiency
• Maximum Likelihood Estimation of Misspecified Models

This page was built for publication: Bias from misspecification of the component variances in a normal mixture