Estimation Problems with Data from a Mixture
Gordon D. Murray, D. Michael Titterington · Journal of the Royal Statistical Society Series C (Applied Statistics) · 1978
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.