ks (1.11.3)

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Kernel Smoothing.


Kernel smoothers for univariate and multivariate data, including densities, density derivatives, cumulative distributions, clustering, classification, density ridges, significant modal regions, and two-sample hypothesis tests. Duong (2017) .

Maintainer: Tarn Duong
Author(s): Tarn Duong <tarn.duong@gmail.com>

License: GPL-2 | GPL-3

Uses: FNN, kernlab, KernSmooth, Matrix, mclust, mgcv, multicool, mvtnorm, maps, misc3d, oz, rgl, MASS, OceanView
Reverse depends: curvHDR, feature, hdrcde, highriskzone, Kernelheaping, npphen, prim, rainbow, TPD, wild1
Reverse suggests: broom, directlabels, fdapace, hdrcde, httk, Infusion, kernelboot, logcondens, rugarch, sensitivity, transport

Released 4 months ago.

42 previous versions



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Related packages: FactoMineR, GPArotation, GenKern, Hmisc, ICSNP, ICS, JADE, KernSmooth, MCMCpack, MNP, Matrix, PTAk, PearsonICA, ROCR, SensoMineR, SparseM, SpatialNP, VGAM, YaleToolkit, abind(20 best matches, based on common tags.)

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