Updating and asymptotic relative efficiency of a nonlinear discriminant function estimated from a mixture of two Gompertz populations

DOI10.1016/S0096-3003(03)00771-9zbMath1054.62074MaRDI QIDQ1883161

S. G. Ramadan, H. M. Moustafa

Publication date: 1 October 2004

Published in: Applied Mathematics and Computation (Search for Journal in Brave)

zbMATH Keywords

asymptotic relative efficiencysimulationsasymptotic expansions of probabilities of misclassificationclassified dataoptimal discriminant functionunclassified data

Mathematics Subject Classification ID

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

Related Items (3)

Estimating parameters of mixtures of multivariate \(t\)-populations and application to classification of observations ⋮ Updating a nonlinear discriminant function estimated from a mixture of two inverse Weibull distributions ⋮ Updating a nonlinear discriminant function estimated from a mixture of two Burr Type III distributions

Cites Work

• Unnamed Item
• Unnamed Item
• Estimation of a discriminant function from a mixture of two gamma distributions when the sample size is small
• Updating a nonlinear discriminant function estimated from a mixture of two Weibull distributions
• The efficiency of a nonlinear discriminant function based on unclassified initial samples from a mixture of two Burr type XII populations
• Updating discriminant functions estimated from inverse gaussian populations
• Variance comparisons for unbiased estimators of probability of correct classification (Corresp.)
• Estimating the Linear Discriminant Function from Initial Samples Containing a Small Number of Unclassified Observations
• Goodness of fit for the extreme value distribution
• The efficiency of a linear discriminant function based on unclassified initial samples
• Normal Discrimination with Unclassified Observations
• On MLE of a nonlinear discriminant function from a mixture of two Gompertz distributions based on small sample size
• Updating a discriminant function on the basis of unclassified data
• Estimating the components of a mixture of normal distributions
• A Survey of Maximum Likelihood Estimation
• Nonparametric Bayes error estimation using unclassified samples
• An Asymptotic Expansion for the Distribution of the Linear Discriminant Function

This page was built for publication: Updating and asymptotic relative efficiency of a nonlinear discriminant function estimated from a mixture of two Gompertz populations