ks (1.11.0)

0 users

Kernel Smoothing.


Kernel smoothers for univariate and multivariate data, including density functions, density derivatives, cumulative distributions, modal clustering, classification (discriminant analysis), significant modal regions and two-sample hypothesis testing.

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

License: GPL-2 | GPL-3

Uses: FNN, kernlab, KernSmooth, Matrix, mclust, mgcv, misc3d, multicool, mvtnorm, OceanView, rgl, oz, MASS
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 5 days ago.

39 previous versions



  (0 votes)


  (0 votes)

Log in to vote.


No one has written a review of ks yet. Want to be the first? Write one now.

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.)

Search for ks on google, google scholar, r-help, r-devel.

Visit ks on R Graphical Manual.