In this paper, a new kernel estimator of multivariate density is proposed by using a univariate kernel function.

This paper discusses childhood growth curve fitting by nonparametric models, and provides two methods for nonparametric curve fitting: smoothing spline and kernel estimator.

The estimator based on kernel principal component extraction requires to stratify the training samples of interested signals with respect to their respective frequencies.