Fast, flexible and user-friendly tools for distribution comparison through direct density ratio estimation. The estimated density ratio can be used for covariate shift adjustment, outlier-detection, change-point detection, classification and evaluation of synthetic data quality. The package implements multiple non-parametric estimation techniques (unconstrained least-squares importance fitting, ulsif(), Kullback-Leibler importance estimation procedure, kliep(), spectral density ratio estimation, spectral(), kernel mean matching, kmm(), and least-squares hetero-distributional subspace search, lhss()). with automatic tuning of hyperparameters. Helper functions are available for two-sample testing and visualizing the density ratios. For an overview on density ratio estimation, see Sugiyama et al. (2012) <doi:10.1017/CBO9781139035613> for a general overview, and the help files for references on the specific estimation techniques.
Version: 0.2.1 Depends: R (≥ 2.10) Imports: osqp, Rcpp, pbapply, ggplot2 LinkingTo: Rcpp, RcppArmadillo, RcppProgress Suggests: knitr, rmarkdown, testthat (≥ 3.0.0) Published: 2025-06-18 DOI: 10.32614/CRAN.package.densityratio Author: Thom Volker [aut, cre], Carlos Gonzalez Poses [ctb], Erik-Jan van Kesteren [ctb] Maintainer: Thom Volker <thombenjaminvolker at gmail.com> BugReports: https://github.com/thomvolker/densityratio/issues License: GPL (≥ 3) URL: https://thomvolker.github.io/densityratio/, https://github.com/thomvolker/densityratio NeedsCompilation: yes Citation: densityratio citation info Materials: README NEWS CRAN checks: densityratio results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=densityratio to link to this page.
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