Implementation of Shannon entropy and Fisher information with Matlab.
- MATLAB 9.7 (MATLAB R2019b)
- Statistics and Machine Learning Toolbox 11.6
- Open
information-analysis.prj
in the Matlab IDE, this will open a new environment for information-analysis project (i.e. add new search paths when openingprj
file, remove paths when closingprj
file) - Modify source code in
src
directory. - Modify m-files in
test
directory to fit your test cases. - Run
run_all_tests
located in thetest
directory to run the tests
- MathWorks Blogs: Complex Step Differentiation
- http://www.johnlapeyre.com/posts/complex-step-differentiation/
- Telesca, L. & Lovallo, M. (2017) On the performance of Fisher Information Measure and Shannon entropy estimators. Physica A: Statistical Mechanics and its Applications, 484, 569–576, Elsevier.