Kernel density estimation for directional–linear data
نویسندگان
چکیده
منابع مشابه
Kernel density estimation for directional-linear data
A nonparametric kernel density estimator for directional–linear data is introduced. The proposal is based on a product kernel accounting for the different nature of both (directional and linear) components of the random vector. Expressions for bias, variance and mean integrated square error (MISE) are derived, jointly with an asymptotic normality result for the proposed estimator. For some part...
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ژورنال
عنوان ژورنال: Journal of Multivariate Analysis
سال: 2013
ISSN: 0047-259X
DOI: 10.1016/j.jmva.2013.06.009