Beaulieu (see ibid., vol.39, no.2, p.193, 1991) states that the equivalence between the generalized multinomial detectors and the generalized weighted partial decision detectors is obscured by E.K. Al-Hussaini (see ibid., vol.37, p.1099, 1989), who concluded that the former outperforms the latter. In reply, Al-Hussaini clarifies his results.>

Finite mixtures of the following ten families of univariate distributions are shown to be identifiable: logarithmic series, discrete rectangular, rectangular, first law of Laplace, noncentralX^{2}, logistic, generalized logistic, generalized hyperbolic-secant, inverse Gaussian, and random walk. A generalized version of a theorem given by Teicher is used to show that the finite mixtures of the following multivariate distributions are also identifiable: negative binomial, logarithmic series, Poisson, normal, inverse Gaussian, and random walk.