KSD: Goodness-of-Fit Tests using Kernelized Stein Discrepancy

An adaptation of Kernelized Stein Discrepancy, this package provides a goodness-of-fit test of whether a given i.i.d. sample is drawn from a given distribution. It works for any distribution once its score function (the derivative of log-density) can be provided. This method is based on "A Kernelized Stein Discrepancy for Goodness-of-fit Tests and Model Evaluation" by Liu, Lee, and Jordan, available at <doi:10.48550/arXiv.1602.03253>.

Version: 1.0.1
Imports: pryr, graphics, stats
Suggests: datasets, ggplot2, gridExtra, mclust, mvtnorm
Published: 2021-01-11
DOI: 10.32614/CRAN.package.KSD
Author: Min Hyung Kang [aut, cre], Qiang Liu [aut]
Maintainer: Min Hyung Kang <Minhyung.Daniel.Kang at gmail.com>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README NEWS
CRAN checks: KSD results


Reference manual: KSD.pdf


Package source: KSD_1.0.1.tar.gz
Windows binaries: r-devel: KSD_1.0.1.zip, r-release: KSD_1.0.1.zip, r-oldrel: KSD_1.0.1.zip
macOS binaries: r-release (arm64): KSD_1.0.1.tgz, r-oldrel (arm64): KSD_1.0.1.tgz, r-release (x86_64): KSD_1.0.1.tgz, r-oldrel (x86_64): KSD_1.0.1.tgz
Old sources: KSD archive


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