A simulative comparison of linear, quadratic and kernel discrimination

DOI10.1080/00949658008810396zbMath0459.62044OpenAlexW2080895822WikidataQ126247264 ScholiaQ126247264MaRDI QIDQ3909847

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Publication date: 1980

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949658008810396

zbMATH Keywords

linear discriminant analysisquadratic discriminant analysisposterior probabilitiessimulative comparisonsmoothness parametersvariable kernel model

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Monte Carlo methods (65C05)

Related Items (13)

Parametric and kernel density methods in discriminant analysis: Another comparison ⋮ A Simulation Study of the Performance of Five Discriminant Analysis Methods for Mixtures of Continuous and Binary Variables ⋮ Smoothing categorical data ⋮ On the use of compactly supported density estimates in problems of discrimination ⋮ A study on discriminant analysis techniques applied to multivariate lognormal data ⋮ Unnamed Item ⋮ On the risk of estimates for block decreasing densities ⋮ A simulation study of imputation techniques in linear quadratic and kernel discriminant analyses ⋮ Projection pursuit discriminant analysis ⋮ Multivariate thin plate spline estimates for the posterior probabilities in the classification problem ⋮ THE EFFECTS OF MISCLASSIFICATION COSTS AND SKEWED DISTRIBUTIONS IN TWO-GROUP CLASSIFICATION ⋮ A new kernel density estimate ⋮ A comparative study of some kernel-based nonparametric density estimators

Cites Work

• Unnamed Item
• Computer-oriented approaches to pattern recognition
• Remarks on Some Nonparametric Estimates of a Density Function
• On the Choice of Smoothing Parameters for Parzen Estimators of Probability Density Functions
• Cases of doubt in allocation problems
• On Estimation of a Probability Density Function and Mode

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