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.
Package details |
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Author | Thom Volker [aut, cre] (ORCID: <https://orcid.org/0000-0002-2408-7820>), Carlos Gonzalez Poses [ctb], Erik-Jan van Kesteren [ctb] |
Maintainer | Thom Volker <thombenjaminvolker@gmail.com> |
License | GPL (>= 3) |
Version | 0.2.0 |
URL | https://thomvolker.github.io/densityratio/ |
Package repository | View on CRAN |
Installation |
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