McLeish, D. L.; Small, Christopher G. Likelihood methods for the discrimination problem. (English) Zbl 0632.62057 Biometrika 73, 397-403 (1986). Suppose independent observations are drawn such that k have a known density g(x) and n-k have a known density f(x). We consider the discrimination problem of allocating observations to their parent densities. The rule minimizing the expected number of misclassifications is written as a function of k and estimators of k are investigated. Properties of the likelihood function of k based upon the order statistics are studied. We conclude that a mixture model analysis performs well regardless of the mechanism, stochastic or deterministic, which generates k and the correct allocation. Cited in 3 Documents MSC: 62H30 Classification and discrimination; cluster analysis (statistical aspects) Keywords:discrimination; misclassifications; likelihood function; order statistics; mixture model; allocation PDFBibTeX XMLCite \textit{D. L. McLeish} and \textit{C. G. Small}, Biometrika 73, 397--403 (1986; Zbl 0632.62057) Full Text: DOI