Proposes non-parametric estimates of the Fisher information measure and the Shannon entropy power. The state-of-the-art studies related to the Fisher-Shannon measures, with new analytical formulas for positive unimodal skewed distributions are presented in Guignard et al. <arXiv:1912.02452>. A 'python' version of this work is available on 'github' and 'PyPi' ('FiShPy').
| Version: | 1.0 |
| Imports: | fda.usc, KernSmooth |
| Published: | 2019-12-16 |
| Author: | Fabian Guignard [aut], Mohamed Laib [aut, cre] |
| Maintainer: | Mohamed Laib <laib.med at gmail.com> |
| License: | MIT + file LICENSE |
| URL: | https://FiShInfo.github.io/ |
| NeedsCompilation: | no |
| CRAN checks: | FiSh results |
| Reference manual: | FiSh.pdf |
| Package source: | FiSh_1.0.tar.gz |
| Windows binaries: | r-devel: FiSh_1.0.zip, r-release: FiSh_1.0.zip, r-oldrel: FiSh_1.0.zip |
| macOS binaries: | r-release: FiSh_1.0.tgz, r-oldrel: FiSh_1.0.tgz |
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