Fast kernel conditional density estimation: A dual-tree Monte Carlo approach
نویسندگان
چکیده
منابع مشابه
Fast kernel conditional density estimation: A dual-tree Monte Carlo approach
We describe a fast, data-driven bandwidth selection procedure for kernel conditional density estimation (KCDE). Specifically, we give aMonte Carlo dual-tree algorithm for efficient, error-controlled approximation of a cross-validated likelihood objective. While exact evaluation of this objective has an unscalableO(n2) computational cost, ourmethod is practical and shows speedup factors as high ...
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ژورنال
عنوان ژورنال: Computational Statistics & Data Analysis
سال: 2010
ISSN: 0167-9473
DOI: 10.1016/j.csda.2010.01.011