Indirect Cross-Validation for Density Estimation
نویسندگان
چکیده
منابع مشابه
Indirect Cross-validation for Density Estimation
A new method of bandwidth selection for kernel density estimators is proposed. The method, termed indirect cross-validation, or ICV, makes use of so-called selection kernels. Least squares cross-validation (LSCV) is used to select the bandwidth of a selection-kernel estimator, and this bandwidth is appropriately rescaled for use in a Gaussian kernel estimator. The proposed selection kernels are...
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• • ~~~~~~ In the setting of nonparametric multivariate density estimation, theorems are established which allow a comparison of the Kullback-Leibler and the Least Squares cross-validation methods of smoothing parameter selection. The family of delta sequence estimators (including kernel, orthogonal series, histogram and histospline estimators) is considered. These theorems also show that eithe...
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ژورنال
عنوان ژورنال: Journal of the American Statistical Association
سال: 2010
ISSN: 0162-1459,1537-274X
DOI: 10.1198/jasa.2010.tm08532