Bias in misspecified mixtures.

Abstract

A finite mixture is a distribution where a given observation can come from any of a finite set of components. That is, the density of the random variable X is of the form f(x) = pi 1f1(x) + pi 2f2(x) + ... + pi kfk(x), where the pi i are the mixing proportions and the fi are the component densities. Mixture models are common in many areas of biology; the… (More)

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Cite this paper

@article{Gray1994BiasIM, title={Bias in misspecified mixtures.}, author={Gerry Gray}, journal={Biometrics}, year={1994}, volume={50 2}, pages={457-70} }