کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
10524495 957560 2005 17 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Convergence rates for unconstrained bandwidth matrix selectors in multivariate kernel density estimation
موضوعات مرتبط
مهندسی و علوم پایه ریاضیات آنالیز عددی
پیش نمایش صفحه اول مقاله
Convergence rates for unconstrained bandwidth matrix selectors in multivariate kernel density estimation
چکیده انگلیسی
Progress in selection of smoothing parameters for kernel density estimation has been much slower in the multivariate than univariate setting. Within the context of multivariate density estimation attention has focused on diagonal bandwidth matrices. However, there is evidence to suggest that the use of full (or unconstrained) bandwidth matrices can be beneficial. This paper presents some results in the asymptotic analysis of data-driven selectors of full bandwidth matrices. In particular, we give relative rates of convergence for plug-in selectors and a biased cross-validation selector.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Multivariate Analysis - Volume 93, Issue 2, April 2005, Pages 417-433
نویسندگان
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