Multistage plug—in bandwidth selection for kernel distribution function estimates

2000 ◽  
Vol 65 (1-4) ◽  
pp. 63-80 ◽  
Author(s):  
Alan M. Polansky ◽  
Edsel R. Baker
Keyword(s):  
Distribution Function ◽  
Bandwidth Selection ◽  
Selection For

On Adaptive Bandwidth Selection for Efficient MIA

2014 ◽  
pp. 82-97 ◽  
Author(s):  
Mathieu Carbone ◽  
Sébastien Tiran ◽  
Sébastien Ordas ◽  
Michel Agoyan ◽  
Yannick Teglia ◽  
...  
Keyword(s):  
Bandwidth Selection ◽  
Selection For ◽  
Adaptive Bandwidth ◽  
Adaptive Bandwidth Selection

scholarly journals New Bandwidth Selection for Kernel Quantile Estimators

2012 ◽  
Vol 2012 ◽  
pp. 1-18
Author(s):  
Ali Al-Kenani ◽  
Keming Yu
Keyword(s):  
Cross Validation ◽  
Kernel Smoothing ◽  
Bandwidth Selection ◽  
Unbiased Estimation ◽  
Optimal Bandwidth ◽  
Squared Error ◽  
Bandwidth Parameter ◽  
Integrated Squared Error ◽  
Selection For ◽  
Quantile Estimators

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.

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