(A) data based algorithm for choosing the bandwidth in the nonparametric estimation = 비모수 추정에서 bandwidth를 선택하는 알고리즘에 관한 연구

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Nonparametric data procedures, by smoothing methods, has been well established as a useful data analytic tool. In particular, theoretical and applied research on nonparametric kemel density estimation has had a noticeable influence on related topics, such as nonparametric regression, nonparametric pattern recognition. Particular application of these nonparametric estimations are crucially dependent on the choice of the bandwidth. Hence various data-driven methods for choosing the bandwidth have been proposed and studied. The most widly studied bandwidth selector is least squares cross-validation. And this methods has attracted many statistical analysis for its practical convient use. But this method consume large amounts of computer time. Even with presentedly computational power, it is all too easy to consume inordinate amounts of computer time by using inefficient algorithms for finding estimates. This article concerns an efficient computational algorithm for this methods when the kernel is symmetric and polynomial functions. In Chapter 2, we discuss for the nonparametric kernel density estimations and we suggest an efficient algorithms for this method. In Chapter 3, we discuss for the nonparametric kernel regression estimations and we suggest an efficient algorithms for this method.
Advisors
Kim, Byung-Chunresearcher김병천researcher
Description
한국과학기술원 : 수학과,
Publisher
한국과학기술원
Issue Date
1993
Identifier
60620/325007 / 000875288
Language
eng
Description

학위논문(박사) - 한국과학기술원 : 수학과, 1993.2, [ 65 p. ]

URI
http://hdl.handle.net/10203/41764
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=60620&flag=dissertation
Appears in Collection
MA-Theses_Ph.D.(박사논문)
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