The efficiency of a nonlinear discriminant function based on unclassified initial samples from a mixture of two Weibull populations

DOI10.1080/00949650410001660793zbMath1059.62066OpenAlexW1965833933MaRDI QIDQ4663385

H. M. Moustafa

Publication date: 30 March 2005

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

Full work available at URL: https://doi.org/10.1080/00949650410001660793

zbMATH Keywords

asymptotic relative efficiencyclassification rulesnonlinear discriminant functionmixture of two Weibull distribution

Mathematics Subject Classification ID

Asymptotic distribution theory in statistics (62E20) Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Cites Work

• Identifiability of finite mixtures using a new transform
• Estimation of a discriminant function from a mixture of two gamma distributions when the sample size is small
• Small sample results for a nonlinear discriminant function estimated from a mixture of two Burr type XII distributions
• Updating a nonlinear discriminant function estimated from a mixture of two Weibull distributions
• Some Efficiency Results for the Estimation of the Mixing Proportion in a Mixture of Two Normal Distributions
• The efficiency of a linear discriminant function based on unclassified initial samples
• Normal Discrimination with Unclassified Observations
• Estimation of Mixed Weibull Parameters in Life Testing
• Estimation of Parameters in Compound Weibull Distributions
• A Survey of Maximum Likelihood Estimation
• An Asymptotic Expansion for the Distribution of the Linear Discriminant Function

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