Practical estimation of multivariate densities using wavelet methods
作者:
K. Tribouley,
期刊:
Statistica Neerlandica
(WILEY Available online 1995)
卷期:
Volume 49,
issue 1
页码: 41-62
ISSN:0039-0402
年代: 1995
DOI:10.1111/j.1467-9574.1995.tb01454.x
出版商: Blackwell Publishing Ltd
关键词: Density estimation;cross validation;wavelet orthonormal bases;Besov spaces
数据来源: WILEY
摘要:
This paper describes a practical method for estimating multivariate densities using wavelets. As in kernel methods, wavelet methods depend on two types of parameters. On the one hand we have a functional parameter: the wavelet Ø (comparable to the kernelK) and on the other hand we have a smoothing parameter: the resolution index (comparable to the bandwidthh). Classically, we determine the resolution index with a cross‐validation method. The advantage of wavelet methods compared to kernel methods is that we have a technique for choosing the wavelet Ø among a fixed family. Moreover, the wavelets method simplifies significantly both the theoretical and the practical computati
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