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Theory and Method

Nonparametric Maximum Likelihood Estimation of a Mixing Distribution

Pages 805-811 | Received 01 Dec 1976, Published online: 05 Apr 2012
 

Abstract

The nonparametric maximum likelihood estimate of a mixing distribution is shown to be self-consistent, a property which characterizes the nonparametric maximum likelihood estimate of a distribution function in incomplete data problems. Under various conditions the estimate is a step function, with a finite number of steps. Its computation is illustrated with a small example.

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