The Relative Information Generating Function-A Quantile Approach
Statistics Theory
2024-12-04 v1 Statistics Theory
Abstract
Information generating functions have been used for generating various entropy and divergence measures. In the present work, we introduce quantile based relative information generating function and study its properties. The proposed generating function provides well-known Kullback-Leibler divergence measure. The quantile based relative information generating function for residual and past lifetimes are presented. A non parametric estimator for the function is derived. A simulation study is conducted to assess performance of the estimators. Finally, the proposed method is applied to a real life data.
Cite
@article{arxiv.2412.02253,
title = {The Relative Information Generating Function-A Quantile Approach},
author = {Sankaran P. G. and Sunoj S. M. and Pavithra Hariharan},
journal= {arXiv preprint arXiv:2412.02253},
year = {2024}
}