ks: Kernel Smoothing

Kernel smoothers for univariate and multivariate data.

AuthorTarn Duong <tarn.duong@gmail.com>
Date of publication2016-06-25 19:07:41
MaintainerTarn Duong <tarn.duong@gmail.com>
LicenseGPL-2 | GPL-3

View on CRAN

Man pages

binning: Linear binning for multivariate data

contour: Contours functions

Hbcv: Biased cross-validation (BCV) bandwidth matrix selector for...

Hlscv: Least-squares cross-validation (LSCV) bandwidth matrix...

Hns: Normal scale bandwidth

Hpi: Plug-in bandwidth selector

Hscv: Smoothed cross-validation (SCV) bandwidth selector

ise.mixt: Squared error bandwidth matrix selectors for normal mixture...

kcde: Kernel cumulative distribution/survival function estimate

kcopula: Kernel copula/copula density estimate

kda: Kernel discriminant analysis

kdde: Kernel density derivative estimate

kde: Kernel density estimate

kde.1d: Functions for univariate kernel density estimates

kde.local.test: Kernel density based local two-sample comparison test

kde.test: Kernel density based global two-sample comparison test

kfe: Kernel functional estimate

kroc: Kernel receiver operating characteristic (ROC) curve

ks-internal: Internal functions in the ks library

ks-package: ks

mixt: Normal and t-mixture distributions

plot.kcde: Plot for kernel cumulative distribution estimate

plot.kda: Plot for kernel discriminant analysis

plot.kdde: Plot for kernel density derivative estimate

plot.kde: Plot for kernel density estimate

plot.kde.loctest: Plot for kernel local significant difference regions

plot.kroc: Plot for kernel receiver operating characteristic curve (ROC)...

plotmixt: Plot for 1- to 3-dimensional normal and t-mixture density...

pre.transform: Pre-sphering and pre-scaling

unicef: Unicef child mortality - life expectancy data

vector: Vector and vector half operators

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.