Nonparametric Maximum Likelihood Estimation of a Mixing Distribution
Journal of the American Statistical AssociationPublished 1 December 1978
Nan M. Laird
Citations733
SJR quartileQ1
SJR score4.10
SNIP3.08
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Abstract
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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Computer ScienceMathematics
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