On nonparametric estimation of a mixing density via the predictive recursion algorithm
arXiv:1812.02149 · doi:10.1007/s13571-019-00206-w
Abstract
Nonparametric estimation of a mixing density based on observations from the corresponding mixture is a challenging statistical problem. This paper surveys the literature on a fast, recursive estimator based on the predictive recursion algorithm. After introducing the algorithm and giving a few examples, I summarize the available asymptotic convergence theory, describe an important semiparametric extension, and highlight two interesting applications. I conclude with a discussion of several recent developments in this area and some open problems.
22 pages, 5 figures. Comments welcome at https://www.researchers.one/article/2018-12-5
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