Robust mixture model cluster analysis using adaptive kernels

DOI10.1080/02664763.2012.740630OpenAlexW1966634478MaRDI QIDQ5128912

J. Andrew Howe, Hamparsum Bozdogan

Publication date: 26 October 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2012.740630

zbMATH Keywords

kernel density estimationrobust estimationunsupervised classificationmixture modelingnon-parametric estimation

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• KernSmooth

Cites Work

• Learning mixture models via component-wise parameter smoothing
• Data. A collection of problems from many fields for the student and research worker
• Informational complexity criteria for regression models.
• Alternating kernel and mixture density estimates.
• Akaike's information criterion and recent developments in information complexity
• Remarks on Some Nonparametric Estimates of a Density Function
• The Method of Moments Applied to a Mixture of Two Exponential Distributions
• Mixture Densities, Maximum Likelihood and the EM Algorithm
• An improvement of the NEC criterion for assessing the number of clusters in a mixture model
• Model-Based Gaussian and Non-Gaussian Clustering
• Comparison of Smoothing Parameterizations in Bivariate Kernel Density Estimation
• Identifiability of Finite Mixtures of Elliptical Distributions
• On Information and Sufficiency
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