Centrality Estimators for Probability Density Functions

arXiv:2404.05816v1 Announce Type: cross
Abstract: In this report, we explore the data selection leading to a family of estimators maximizing a centrality. The family allows a nice properties leading to accurate and robust probability density function fitting according to some criteria we define. We establish a link between the centrality estimator and the maximum likelihood, showing that the latter is a particular case. Therefore, a new probability interpretation of Fisher maximum likelihood is provided. We will introduce and study two …

abstract arxiv cs.lg data estimator explore family function functions math.st nice probability report robust stat.th type