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
Repository: https://mauriziofilippone.r-universe.dev
Date/Publication: 2026-08-30 09:36:23 UTC
RemoteUrl: https://github.com/mauriziofilippone/epkde
RemoteRef: HEAD
RemoteSha: 23e76bece79b7aece180b842e597d52ee10ae401
NeedsCompilation: no
Packaged: 2026-10-11 10:08:23 UTC; root