A comparison of the \(L_2\) minimum distance estimator and the EM-algorithm when fitting \(k\)-component univariate normal mixtures

DOI10.1007/s00362-016-0747-xzbMath1416.62148OpenAlexW2461722470MaRDI QIDQ1685303

Robert Hammarstrand, Thomas Davidson, Brenton R. Clarke

Publication date: 13 December 2017

Published in: Statistical Papers (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00362-016-0747-x

zbMATH Keywords

EM algorithmminimum distance estimationMonte Carlo simulationrobust estimation

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Point estimation (62F10)

Related Items (1)

Mixtures of multivariate contaminated normal regression models

Uses Software

• R
• EMMIX-skew
• mixtools
• EMMIX
• nleqslv
• Emmixuskew

Cites Work

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• A comparison of some methods for estimating mixed normal distributions
• Robust Statistics
• A cautionary note on likelihood ratio tests in mixture models

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