DATA-DEPENDENT BANDWIDTH CHOICE FOR A GRADE DENSITY KERNEL ESTIMATE

被引：20

作者：

CWIK, J ^{[1
]}

MIELNICZUK, J ^{[1
]}

机构：

[1] POLISH ACAD SCI,INST COMP SCI,PL-01237 WARSAW,POLAND

来源：

STATISTICS & PROBABILITY LETTERS | 1993年 / 16卷 / 05期

关键词：

DATA-DEPENDENT BANDWIDTH; GRADE DENSITY; MEAN INTEGRATED SQUARE ERROR;

D O I：

10.1016/0167-7152(93)90074-S

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

The method of choosing a smoothing parameter for a grade density kernel estimate g is proposed. It consists in estimating the minimizer of the asymptotic MISE for two main terms in the expansion of g. The behaviour of the estimates incorporating proposed bandwidths is investigated in the variety of parametric models and compared with that of estimates using bandwidths suitable for the complete observability case. They are shown to perform well for unimodal densities and moderately well for multimodal ones.

引用

页码：397 / 405

页数：9

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