Asymptotic Error Rates for Point Process Classification

Autor:	Rong, Xinhui, Solo, Victor
Rok vydání:	2024
Předmět:	Mathematics - Statistics Theory Electrical Engineering and Systems Science - Signal Processing
Druh dokumentu:	Working Paper
Popis:	Point processes are finding growing applications in numerous fields, such as neuroscience, high frequency finance and social media. So classic problems of classification and clustering are of increasing interest. However, analytic study of misclassification error probability in multi-class classification has barely begun. In this paper, we tackle the multi-class likelihood classification problem for point processes and develop, for the first time, both asymptotic upper and lower bounds on the error rate in terms of computable pair-wise affinities. We apply these general results to classifying renewal processes. Under some technical conditions, we show that the bounds have exponential decay and give explicit associated constants. The results are illustrated with a non-trivial simulation. Comment: 25 pages, 3 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2403.12531 Zobrazit plný text záznamu View this record from Arxiv