Package: ksm 1.1

Leo Belzile

ksm: Kernel Density Estimation for Random Symmetric Positive Definite Matrices

Kernel smoothing for Wishart random matrices described in Daayeb, Khardani and Ouimet (2025) <doi:10.48550/arXiv.2506.08816>, Gaussian and log-Gaussian models using least square or likelihood cross validation criteria for optimal bandwidth selection.

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

ksm_1.1.tar.gz
ksm_1.1.tar.gz(r-4.7-arm64)ksm_1.1.tar.gz(r-4.7-x86_64)ksm_1.1.tar.gz(r-4.6-arm64)ksm_1.1.tar.gz(r-4.6-x86_64)
ksm_1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
ksm/json (API)
NEWS

# Install 'ksm' in R:
install.packages('ksm', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/lbelzile/ksm/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:
  • realvar - Realized variance of Amazon and SPY

On CRAN:

Conda:

openblascppopenmp

3.00 score 130 downloads 37 exports 2 dependencies

Last updated from:d1a4ea325d. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK177
linux-devel-x86_64OK129
source / vignettesOK238
linux-release-arm64OK144
linux-release-x86_64OK131
wasm-releaseOK115

Exports:bandwidth_optimdinvWishartdmbeta2dsmlnormdsmnormdWishartintegrate_spdkdens_smlnormkdens_smnormkdens_symmatkdens_Wishartlcv_kdens_symmatlcv_kern_smlnormlcv_kern_smnormlcv_kern_Wishartlscv_kdens_symmatlscv_kern_smlnormlscv_kern_smnormlscv_kern_WishartmgammaRiccatirinvWishartrmbeta2rmnormrotation_scalingrotation2drotation3drVARrWARrWishartsimu_fdenssimu_ise_montecarlosimu_kldivsimu_rdenssumlogsumsignedlogsymmetrize

Dependencies:RcppRcppArmadillo

Overview of the ksm package

Leo Belzile

Rendered fromvignette_ksm.Rmdusingknitr::rmarkdownon Jun 07 2026.

Last update: 2026-06-07
Started: 2026-06-07

Readme and manuals

Help Manual

Help pageTopics
Bandwidth optimization for symmetric matrix kernelsbandwidth_optim
Density of inverse Wishart random matrixdinvWishart
Matrix beta type II density functiondmbeta2
Symmetric matrix-variate lognormal densitydsmlnorm
Symmetric matrix-variate normal densitydsmnorm
Density of Wishart random matrixdWishart
Integration with respect to symmetric positive definite matricesintegrate_spd
Symmetric matrix log-normal kernel densitykdens_smlnorm
Symmetric matrix normal kernel densitykdens_smnorm
Kernel density estimators for symmetric matriceskdens_symmat
Wishart kernel densitykdens_Wishart
Likelihood cross-validation for symmetric positive definite matrix kernelslcv_kdens_symmat
Likelihood cross validation criterion for symmetric matrix lognormal kernellcv_kern_smlnorm
Likelihood cross validation criterion for symmetric matrix normal kernellcv_kern_smnorm
Likelihood cross validation criterion for Wishart kernellcv_kern_Wishart
Least square cross-validation for symmetric positive definite matrix kernelslscv_kdens_symmat
Least square cross validation criterion for log symmetric matrix normal kernellscv_kern_smlnorm
Least square cross validation criterion for matrix normal kernellscv_kern_smnorm
Least square cross validation criterion for Wishart kernellscv_kern_Wishart
Multivariate gamma functionmgamma
Realized variance of Amazon and SPYrealvar
Solver for Riccati equationRiccati
Random matrix generation from the inverse Wishart distributionrinvWishart
Random matrix generation from matrix beta type II distributionrmbeta2
Random vector generation from the multivariate normal distributionrmnorm
Random matrix generation from first-order autoregressive Wishart processrWAR
Random matrix generation from Wishart distributionrWishart
Symmetrize matrixsymmetrize