A mixture of mixture models for a classification problem: the unity measure error

DOI10.1016/j.csda.2006.01.001zbMath1161.62373OpenAlexW1978692121MaRDI QIDQ1019886

Marco Di Zio, Ugo Guarnera, Roberto Rocci

Publication date: 29 May 2009

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

Full work available at URL: https://doi.org/10.1016/j.csda.2006.01.001

zbMATH Keywords

EM algorithmmixture modelseditingsystematic error

Mathematics Subject Classification ID

Related Items (9)

Fitting insurance and economic data with outliers: a flexible approach based on finite mixtures of contaminated gamma distributions ⋮ Bayesian clustering of skewed and multimodal data using geometric skewed normal distributions ⋮ Outlier detection in multivariate functional data through a contaminated mixture model ⋮ Robust model-based clustering with mild and gross outliers ⋮ A two-step estimator for multilevel latent class analysis with covariates ⋮ Gaussian mixture modeling and model-based clustering under measurement inconsistency ⋮ Distributionally robust polynomial chance-constraints under mixture ambiguity sets ⋮ Parsimonious mixtures of multivariate contaminated normal distributions ⋮ A multiple imputation approach to deal with the unity measure error

Uses Software

• R

Cites Work

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• Choosing starting values for the EM algorithm for getting the highest likelihood in multivariate Gaussian mixture models
• Another interpretation of the EM algorithm for mixture distributions
• Exact mean integrated squared error
• Maximum likelihood estimation via the ECM algorithm: A general framework
• Distributions Generated by Perturbation of Symmetry with Emphasis on a Multivariate Skewt-Distribution
• Identifiability of Finite Mixtures
• On the Identifiability of Finite Mixtures

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