np - Nonparametric Kernel Smoothing Methods for Mixed Data Types
Nonparametric (and semiparametric) kernel methods that
seamlessly handle a mix of continuous, unordered, and ordered
factor data types. We would like to gratefully acknowledge
support from the Natural Sciences and Engineering Research
Council of Canada (NSERC, <https://www.nserc-crsng.gc.ca/>),
the Social Sciences and Humanities Research Council of Canada
(SSHRC, <https://www.sshrc-crsh.gc.ca/>), and the Shared
Hierarchical Academic Research Computing Network (SHARCNET,
<https://sharcnet.ca/>). We would also like to acknowledge the
contributions of the GNU GSL authors. In particular, we adapt
the GNU GSL B-spline routine gsl_bspline.c adding automated
support for quantile knots (in addition to uniform knots),
providing missing functionality for derivatives, and for
extending the splines beyond their endpoints.
