Estimation Problems with Data from a Mixture

The problem of estimating density functions using data from different distributions, and a mixture of them, is considered. Maximum likelihood and Bayesian parametric techniques are summarized and various approaches using distribution‐free kernel methods are expounded. A comparative study is made using the halibut data of Hosmer (1973) and the problem of incomplete data is briefly discussed.

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