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Proposes non-parametric estimates of the Fisher information measure and the Shannon entropy power. More theoretical and implementation details can be found in Guignard et al. <doi:10.3389/feart.2020.00255>. A 'python' version of this work is available on 'github' and 'PyPi' ('FiShPy').
| Version: | 1.1 |
| Imports: | fda.usc, KernSmooth |
| Published: | 2021-05-03 |
| DOI: | 10.32614/CRAN.package.FiSh |
| Author: | Fabian Guignard [aut], Mohamed Laib [aut, cre] |
| Maintainer: | Mohamed Laib <laib.med at gmail.com> |
| License: | MIT + file LICENSE |
| NeedsCompilation: | no |
| CRAN checks: | FiSh results |
| Reference manual: | FiSh.pdf |
| Package source: | FiSh_1.1.tar.gz |
| Windows binaries: | r-devel: FiSh_1.1.zip, r-release: FiSh_1.1.zip, r-oldrel: FiSh_1.1.zip |
| macOS binaries: | r-release (arm64): FiSh_1.1.tgz, r-oldrel (arm64): FiSh_1.1.tgz, r-release (x86_64): FiSh_1.1.tgz, r-oldrel (x86_64): FiSh_1.1.tgz |
| Old sources: | FiSh archive |
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