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Variable Kernel Estimates of Multivariate Densities

 

作者: Leo Breiman,   William Meisel,   Edward Purcell,  

 

期刊: Technometrics  （Taylor Available online 1977）
卷期: Volume 19, issue 2  

页码: 135-144

 

ISSN:0040-1706

 

年代: 1977

 

DOI:10.1080/00401706.1977.10489521

 

出版商: Taylor & Francis Group

 

关键词: Density estimation;Kernel density estimation

 

数据来源: Taylor

 

摘要:

A class of density estimates using a superposition of kernels where the kernel parameter can depend on the nearest neighbor distances is studied by the use of simulated data. Their performance using several measures of error is superior to that of the usual Parzen estimators. A tentative solution is given to the problem of calibrating the kernel peakedness when faced with a finite sample set.

 

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