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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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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.