Asymptotic Classification Error for Heavy-Tailed Renewal Processes

TL;DR

This paper derives asymptotic expressions for the misclassification error bounds of heavy-tailed renewal processes, advancing understanding of classification error probabilities in point process data.

Contribution

It provides the first asymptotic analysis of classification error bounds specifically for heavy-tailed renewal processes.

Findings

Derived asymptotic expressions for Bhattacharyya bound

Analyzed error probabilities for heavy-tailed renewal processes

Enhanced theoretical understanding of point process classification

Abstract

Despite the widespread occurrence of classification problems and the increasing collection of point process data across many disciplines, study of error probability for point process classification only emerged very recently. Here, we consider classification of renewal processes. We obtain asymptotic expressions for the Bhattacharyya bound on misclassification error probabilities for heavy-tailed renewal processes.