ksm

Kernel Density Estimation for Random Symmetric Positive Definite Matrices

Kernel smoothing for Wishart random matrices described in Daayeb, Khardani and Ouimet (2025) , Gaussian and log-Gaussian models using least square or likelihood cross validation criteria for optimal bandwidth selection.

Kernel Density Estimation for Random Symmetric Positive Definite Matrices

An R package with Wishart, log-Gaussian and Gaussian kernels for positive definite matrices, with optimal bandwidth selection based on least square cross validation or leave-one-out cross-validation criteria.

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.
install.packages("ksm")

1.1 by Leo Belzile, 4 months ago

Report a bug at https://github.com/lbelzile/ksm/issues

Browse source code at https://github.com/cran/ksm

Authors: Leo Belzile [aut, cre] , Frederic Ouimet [aut]

Documentation:   PDF Manual  

MIT + file LICENSE license

Imports Rcpp

Suggests cubature, rmarkdown, knitr, tinytest

Linking to Rcpp, RcppArmadillo

See at CRAN

R links

R homepage

Download R

Mailing lists

R documentation

R manuals

R FAQs

The R Journal

CRAN links

CRAN homepage

CRAN repository policy

Submit a package

METACRAN stuff

About METACRAN

At github

Report a bug