The β-divergence for Bandwidth Selection in Circular Kernel Density Estimation.

The choice of bandwidth is crucial in circular kernel density estimation. Various bandwidth selection techniques have been proposed in the literature. New bandwidth selectors based on the measure β -divergence for kernel density estimation with circular data are presented in this work. These selectors are obtained by minimizing the mean of the measure β -divergence between the density to be estimated and its estimator. The idea is based on the generalization of the standard method which selects the bandwidth by minimizing the mean integrated squared error (MISE). The performance of the proposed selectors is evaluated through a simulation study and compared with other existing selectors. These selectors are illustrated with some real datasets. [ABSTRACT FROM AUTHOR]