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Consider two kernel density estimates having the same bandwidth but two different kernels. The criterion which minimizes the L 1 distance between these two estimates is known as the double kernel method. In this work, instead of the L 1 distance, we use the L 2 one. Asymptotic behavior of this criterion and the corresponding bandwidth are investigated. It is shown that the L 2 double kernel method and the least-squares cross-validation technique have almost the same properties. An implementation of the method is also proposed.
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Belkacem Abdous (1999) studied this question.
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