FiSh-package: FiSh: Fisher-Shannon method

In fishinfo/FiSh: Fisher-Shannon method

Description

Proposes non-parametric estimates of the Fisher Information Measure and the Shannon Entropy Power. A Python version of this work is available on GitHub and PyPi (FiShPy).

Details

This R code was developed and used for the following paper: F. Guignard, M. Laib, F. Amato, M. Kanevski, Advanced analysis of temporal data using Fisher-Shannon information : theoretical development and application to geoscience, In prep.

Author(s)

Fabian Guignard [e-mail] and

Mohamed Laib [e-mail]

Maintainer: Mohamed Laib [e-mail]

References

S. J. Sheather and M. C. Jones (1991). A reliable data-based bandwidth selection method for kernel density estimation. Journal of the Royal Statistical Society, Series B, 53, 683 - 690.

M. P. Wand and M. C. Jones (1995). Kernel Smoothing. Chapman and Hall, London.

C. Vignat, J.F Bercher (2003). Analysis of signals in the Fisher–Shannon information plane, Physics Letters A, 312, 190, 27 – 33.

F. Guignard, M. Laib, F. Amato, M. Kanevski, Advanced analysis of temporal data using Fisher-Shannon information : theoretical development and application to geoscience, In prep.

See Also

Useful links:

• https://FiShInfo.github.io/

fishinfo/FiSh documentation built on Jan. 2, 2020, 2:24 p.m.