Testing for outliers from a mixture distribution when some data are missing

DOI10.1016/S0167-9473(03)00008-2zbMath1429.62270MaRDI QIDQ956746

Wayne A. Woodward, Stephan R. Sain

Publication date: 26 November 2008

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

zbMATH Keywords

EM algorithmmissing datamixture modeloutlier detection

Mathematics Subject Classification ID

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

Related Items (4)

Drug risk assessment with determining the number of sub-populations under finite mixture normal models ⋮ Editorial: Advances in mixture models ⋮ Kernel ellipsoidal trimming ⋮ Outlier detection under star-contoured errors

Uses Software

• MULTIMIX
• bootstrap

Cites Work

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• Mixture model clustering for mixed data with missing information
• Fitting a mixture model to three-mode three-way data with missing information
• Mixture Densities, Maximum Likelihood and the EM Algorithm
• Finding Groups in Data
• Mixture model clustering using the MULTIMIX program

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