We generalize the Point information gain (PIG) and derived quantities, i.e. Point information entropy (PIE) and Point information entropy density (PIED), for the case of R\'enyi entropy and simulate the behavior of PIG for typical distributions. We also use these methods for the analysis of multidimensional datasets. We demonstrate the main properties of PIE/PIED spectra for the real data on the example of several images, and discuss possible further utilization in other fields of data processing.
@article{arxiv.1501.02891,
title = {Point Information Gain and Multidimensional Data Analysis},
author = {Renata Rychtáriková and Jan Korbel and Petr Macháček and Petr Císař and Jan Urban and Dmytro Soloviov and Dalibor Štys},
journal= {arXiv preprint arXiv:1501.02891},
year = {2016}
}