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.
- Version0.60-17
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?Yes
- np citation info
- Last release03/13/2023
Documentation
Team
Jeffrey S. Racine
Tristen Hayfield
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Last 30 days
This package has been downloaded 7,424 times in the last 30 days. Impressive! The kind of number that makes colleagues ask, 'How did you do it?' The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 255 times.
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Last 365 days
This package has been downloaded 76,791 times in the last 365 days. This work is reaching a lot of screens. A significant achievement indeed! The day with the most downloads was May 01, 2024 with 642 downloads.
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- Imports4 packages
- Suggests3 packages
- Reverse Depends9 packages
- Reverse Imports23 packages
- Reverse Suggests4 packages