A criterion based on the Mahalanobis distance for cluster analysis with subsampling

DOI10.1007/s00357-012-9100-9zbMath1360.62349OpenAlexW1970841552MaRDI QIDQ263330

Avner Bar-Hen, Nicolas Picard

Publication date: 4 April 2016

Published in: Journal of Classification (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00357-012-9100-9

zbMATH Keywords

model-based clusteringcluster analysissubsamplingMahalanobis distancespecies classificationvariance criterion

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to environmental and related topics (62P12)

Uses Software

• flexmix
• AS 136

Cites Work

• Algorithm AS 136: A K-Means Clustering Algorithm
• A maximum likelihood methodology for clusterwise linear regression
• Identifiability of finite mixtures of multinomial logit models with varying and fixed effects
• A classification EM algorithm for clustering and two stochastic versions
• The Influence Curve and Its Role in Robust Estimation
• Model-Based Gaussian and Non-Gaussian Clustering
• Model-Based Clustering, Discriminant Analysis, and Density Estimation
• Almost Nonparametric Inference for Repeated Measures in Mixture Models
• On the estimation of the influence curve
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