Package: np 0.60-17

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.

Authors:Jeffrey S. Racine [aut, cre], Tristen Hayfield [aut]

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Bug tracker:https://github.com/jeffreyracine/r-package-np/issues

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Exports:b.stargradientsnpcdensnpcdensbwnpcdistnpcdistbwnpcmstestnpconmodenpcopulanpdeneqtestnpdeptestnpindexnpindexbwnpksumnpplotnpplregnpplregbwnpqcmstestnpqregnpquantilenpregnpregbwnpregivnpregivderivnpscoefnpscoefbwnpsdeptestnpseednpsigtestnpsymtestnptgaussnpudensnpudensbwnpudistnpudistbwnpuniden.boundarynpuniden.reflectnpuniden.scnpunitestseuocquantile

Dependencies:bootcubaturelatticeMASSMatrixMatrixModelsquadprogquantregRcppSparseMsurvival