Package: FiSh
Type: Package
Title: Fisher-Shannon Method
Version: 1.0
Authors@R: c(
  person("Fabian","Guignard", role=c("aut"), email="fabian.guignard@bluemail.ch"),
  person("Mohamed","Laib", role=c("aut","cre"), email="laib.med@gmail.com"))
Author: Fabian Guignard [aut],
  Mohamed Laib [aut, cre]
Maintainer: Mohamed Laib <laib.med@gmail.com>
Description: 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').
Imports: fda.usc, KernSmooth
License: MIT + file LICENSE
URL: https://FiShInfo.github.io/
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Note: The authors are grateful to Mikhail Kanevski, Federico Amato and
        Luciano Telesca for many fruitful discussions about the use and
        the application of Fisher-Shannon method.
NeedsCompilation: no
Packaged: 2019-12-10 10:47:05 UTC; laib
Repository: CRAN
Date/Publication: 2019-12-16 14:00:09 UTC
