Package: epkde
Type: Package
Title: Bayesian Bandwidth Selection for Multivariate KDE via
        Expectation Propagation
Version: 0.1.0
Authors@R: person("Maurizio", "Filippone", email = "maurizio.filippone@kaust.edu.sa", role = c("aut", "cre"))
Author: Maurizio Filippone [aut, cre]
Maintainer: Maurizio Filippone <maurizio.filippone@kaust.edu.sa>
Description: Implements the approximate Bayesian method for bandwidth selection
    in multivariate kernel density estimation (KDE) proposed in Filippone &
    Sanguinetti (2011) <doi:10.1016/j.csda.2011.05.023>. The method uses the
    Expectation Propagation (EP) algorithm to approximate the posterior
    distribution of the inverse bandwidth (precision matrix) under a
    leave-one-out cross-validated likelihood. Three covariance structures are
    supported: isotropic (scalar precision), diagonal, and full precision
    matrix. Online Bayesian updating is supported for the isotropic case.
    The approximate posterior can be used for bandwidth selection, model
    comparison (via the model evidence / Bayes factor), and online learning.
Depends: R (>= 4.0.0)
License: GPL-3
Encoding: UTF-8
Imports:
Suggests: ks, testthat (>= 3.0.0), knitr, rmarkdown
Config/testthat/edition: 3
RoxygenNote: 7.3.2
VignetteBuilder: knitr
URL: https://github.com/mauriziofilippone/epkde
BugReports: https://github.com/mauriziofilippone/epkde/issues
NeedsCompilation: no
Packaged: 2026-08-30 09:29:08 UTC; filippm
Repository: CRAN
Date/Publication: 2026-09-10 13:10:08 UTC
Built: R 4.7.0; ; 2026-09-10 23:51:50 UTC; windows
