print.fk_regression

Print method for kernel regression estimate obtained with function fk_regression()

file

Implements the method of Hofmeyr, D.P. (2021) <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.
The package is accompanied by an instructive paper in the Journal of Statistical Software <doi:10.18637/jss.v101.i03>.

David Hofmeyr

FKSUM

Fast Kernel Sums

print.fk_regression function

<dl> <dt>x</dt>
<dd>an object of class fk_regression, output from the function of the same name.</dd> <dt>...</dt>
<dd>(optional) further arguments passed to or from other methods.</dd></dl>

Arguments

Print method for class fk_regression — print.fk_regression

<dl>

 <dt>x</dt>
<dd>an object of class fk_regression, output from the function of the same name.</dd>

 <dt>...</dt>
<dd>(optional) further arguments passed to or from other methods.</dd>

</dl>

print.fk_regression: Print method for class fk_regression

Description

Usage

Arguments