Cross Validation Bandwidth Selection for Derivatives of Multidimensional Densities

2014 ◽  
Author(s):  
Matthew Baird
2012 ◽  
Vol 2012 ◽  
pp. 1-18
Author(s):  
Ali Al-Kenani ◽  
Keming Yu

We propose a cross-validation method suitable for smoothing of kernel quantile estimators. In particular, our proposed method selects the bandwidth parameter, which is known to play a crucial role in kernel smoothing, based on unbiased estimation of a mean integrated squared error curve of which the minimising value determines an optimal bandwidth. This method is shown to lead to asymptotically optimal bandwidth choice and we also provide some general theory on the performance of optimal, data-based methods of bandwidth choice. The numerical performances of the proposed methods are compared in simulations, and the new bandwidth selection is demonstrated to work very well.


Author(s):  
Mathieu Carbone ◽  
Sébastien Tiran ◽  
Sébastien Ordas ◽  
Michel Agoyan ◽  
Yannick Teglia ◽  
...  

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