Nonparametric discrimination procedures for non-normal distributions

DOI10.1080/00949657908810272zbMath0412.62042OpenAlexW1971831029MaRDI QIDQ4199377

Douglas A. Penfield, Stephen L. Koffler

Publication date: 1978

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

Full work available at URL: https://doi.org/10.1080/00949657908810272

zbMATH Keywords

Monte Carlo methodsrelative efficiencynon-normal datalinear discriminant functionlog normalquadratic discriminantclassification analysisGessaman density estimatorinverse hyperbolic sine normalLoftsgaarden-Quesenberry density estimatorlogit normalnearest neighbor procedurenonparametric discrimination proceduresParzen- Cacoullos density estimator

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Monte Carlo methods (65C05)

Related Items (5)

The johnson translation system in monte carlo studies ⋮ A comparison of the classical and the linear programming approaches to the classification problem in discriminant analysis ⋮ Minimum Hellinger distance estimators for multivariate distributions from the Johnson system ⋮ The rank transformation as a method of discrimination with some examples ⋮ A general approach to classification problems

Cites Work

• Estimation of a multivariate density
• Robustness of the linear and quadratic discriminant function to certain types of non‐normality
• A Nonparametric Estimate of a Multivariate Density Function
• Uniform Random Number Generators
• A Consistent Nonparametric Multivariate Density Estimator Based on Statistically Equivalent Blocks
• A Comparison of Some Multivariate Discrimination Procedures
• On Estimation of a Probability Density Function and Mode

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