Finite mixtures of the following ten families of univariate distributions are shown to be identifiable: logarithmic series, discrete rectangular, rectangular, first law of Laplace, noncentralX², 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.
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AL-Hussaini et al. (1981) studied this question.
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