Packaged: Wed May  2 10:34:30 2007; jracine

Author: Tristen Hayfield <hayfield@phys.ethz.ch>, Jeffrey S. Racine <racinej@mcmaster.ca>
Packaged: Tue Dec 18 11:42:22 2007; jracine

Packaged: Fri Jan 11 11:05:00 2008; jracine

Packaged: Wed Apr 30 15:27:00 2008; jracine

Title: Nonparametric kernel smoothing methods for mixed data types
Description: This package provides a variety of 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:www.nserc.ca), the Social Sciences and Humanities Research Council of Canada (SSHRC:www.sshrc.ca), and the Shared Hierarchical Academic Research Computing Network (SHARCNET:www.sharcnet.ca).
Packaged: Fri Jul 25 10:02:49 2008; jracine

Packaged: Tue Aug 12 10:21:07 2008; jracine

Packaged: Sat Nov  1 02:11:08 2008; jracine

Packaged: Fri Nov 14 07:34:58 2008; jracine

Packaged: Wed Nov 19 14:39:57 2008; jracine

Packaged: Thu Jan 15 11:15:13 2009; jracine

Packaged: Thu Jan 29 14:00:46 2009; jracine

Author: Tristen Hayfield <hayfield@phys.ethz.ch>, Jeffrey S. Racine
Description: This package provides a variety of 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:www.nserc.ca), the Social Sciences and Humanities
Research Council of Canada (SSHRC:www.sshrc.ca), and the Shared
Hierarchical Academic Research Computing Network

Author: Tristen Hayfield <hayfield@mpia.de>, Jeffrey S. Racine

person(given = "Tristen", family = "Hayfield", role = c("aut"), email = "tristen.hayfield@gmail.com"))
Description: This package provides a variety of 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:www.nserc.ca), the Social Sciences and Humanities Research Council of Canada (SSHRC:www.sshrc.ca), and the Shared Hierarchical Academic Research Computing Network (SHARCNET:www.sharcnet.ca).