Asymptotic Optimality of Likelihood-Based Cross-Validation
نویسندگان
چکیده
منابع مشابه
Asymptotic optimality of likelihood-based cross-validation.
Likelihood-based cross-validation is a statistical tool for selecting a density estimate based on n i.i.d. observations from the true density among a collection of candidate density estimators. General examples are the selection of a model indexing a maximum likelihood estimator, and the selection of a bandwidth indexing a nonparametric (e.g. kernel) density estimator. In this article, we estab...
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co(A): the convex hull of a set A, supp(Q): the support of a measure Q ∈ M, suppP(g(X θ)): the support of g(X θ) when X is distributed according to P ∈ M, s(Q θ): the dimension of the co(suppP(g(X θ))). The principal challenge in deriving our optimality result is establishing part (a) of Theorem 3.1. For ease of exposition, we provide an outline of the proof of this claim before its formal deri...
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ژورنال
عنوان ژورنال: Statistical Applications in Genetics and Molecular Biology
سال: 2004
ISSN: 1544-6115
DOI: 10.2202/1544-6115.1036