NWmat

a vector of gridpoints to evaluate estimate at

xgrid

a vector containing the predictor data

a character string naming the kernel function

kernel

This function computes the A matrix for use in quadprog. This
matrix corresponds to the derivative matrix for constrained
sharpening in the monotonic regression problem.

models

Functions and data sets inspired by data sharpening -
data perturbation to achieve improved performance in
nonparametric estimation, as described in Choi, E., Hall, P.
and Rousson, V. (2000) <doi:10.1214/aos/1015957396>.
Capabilities for enhanced local linear regression function
and derivative estimation are included, as well as an
asymptotically correct iterated data sharpening estimator
for any degree of local polynomial regression estimation.
A cross-validation-based bandwidth selector is included which,
in concert with the iterated sharpener, will often provide
superior performance, according to a median integrated squared
error criterion. Sample data sets are provided to illustrate
function usage.

NWmat: Smoother Matrix for Nadaraya-Watson Local Constant Regression

Description

Usage

Arguments

Value