K-nearest neighbour kernel density estimation, the choice of optimal k

[1] BOWMAN, A. W.: An alternative method cross-validation for the smoothing of density estimates, Biometrika 71 (1984), 353-360.10.1093/biomet/71.2.353Search in Google Scholar

[2] GYÖRFI, L.: On the rate of convergence of nearest neighbor rules, IEEE Trans. Inform. Theory 24 (1978), 509-512.10.1109/TIT.1978.1055898Search in Google Scholar

[3] GYÖRFI, L.: The rate of convergence of kn-nn regression estimates and classification rules, IEEE Trans. Inform. Theory 27 (1981), 362-364.10.1109/TIT.1981.1056344Search in Google Scholar

[4] MACK, Y. P.-ROSENBLATT, M.: Multivariate k-nearest neighbour density estimates, J. Multivariate Anal. 9 (1979), 1-15.10.1016/0047-259X(79)90065-4Search in Google Scholar

[5] ORAVA, J.: K-nearest neighbour kernel density estimation, the choice of optimal k, Biometrika (accepted).Search in Google Scholar

[6] VAN RYZIN, J.: On strong consistency of density estimates, Ann. Math. Statist. 40 (1969), 1765-1772.10.1214/aoms/1177697388Search in Google Scholar

[7] WAND, M. P.-JONES, M. C.: Kernel Smothing. Chapman and Hall, London, 1995.10.1007/978-1-4899-4493-1Search in Google Scholar