norm_K

<p>numeric vector of positive coefficients.</p>

beta

<p>Computes the L2 norm of a kernel implemented in FKSUM, based on its coefficients. NB: the coefficients will first be normalised so that
  the kernel represents a density function. Equivalent to sqrt(roughness_K())</p>

file

Implements the method of Hofmeyr, D.P. (2019) <DOI:10.1109/TPAMI.2019.2930501> for fast evaluation of univariate kernel smoothers based on recursive computations.
Applications to the basic problems of density and regression function estimation are provided, as well as some projection pursuit methods
for which the objective is based on non-parametric functionals of the projected density, or conditional density of a response given projected
covariates.

norm_K: The L2 norm of a kernel

Description

Usage

Arguments

Value

References