AN EFFECTIVE BANDWIDTDTH SELECTOR IN A COMPLICATED KERNEL REGRESSION

The field of nonparametrics has shown its appeal in re-cent years with anarray of new tools for statistical analysis. As one of those tools nonparametric regression has become a prominent statis-tical research topic and also has been well established as a useful tool. In this article we investigate the biased cross-validation selector, BCV, which is proposed by Oh et al. (1995) for a less smoothing regression function. In the simulation study BCV selector is shown to perform well in parctice with respect to ASE ratio.