Robust multivariate classification procedures based on the mml estimators

DOI10.1080/03610928408828734zbMath0572.62049OpenAlexW2066642518MaRDI QIDQ3690027

Narayanaswamy Balakrishnan, Moti L. Tiku

Publication date: 1984

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610928408828734

zbMATH Keywords

normal populationsnon-normalitydensity estimateserrors of misclassificationtesting hypothesisrobust classificationmodified maximum likelihood estimationclassification proceduredistribution- free procedures

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Robustness and adaptive procedures (parametric inference) (62F35)

Related Items (6)

Testing the equality of variance-covariance matrices the robust way ⋮ Some robust procedures for comparing several straight lines under heteroscedasticity and non-normality ⋮ Robust classification procedures based on the mml estimators ⋮ Projection-pursuit approach to robust linear discriminant analysis ⋮ The location model for mixtures of categorical and continuous variables ⋮ Robust classification procedures based on dichotomous and continuous variables

Cites Work

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• A Nonparametric Estimate of a Multivariate Density Function
• Monte Carlo study of some simple estimators in censored normal samples
• Some Results on the Distribution of Two Random Matrices Used in Classification Procedures
• A Consistent Nonparametric Multivariate Density Estimator Based on Statistically Equivalent Blocks
• An Asymptotic Expansion for the Distribution of the Linear Discriminant Function
• On the Distribution of two Random Matrices used in Classification Procedures

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