On goodness-of-fit testing for self-exciting point processes
Statistics Theory
2024-07-15 v1 Methodology
Statistics Theory
Abstract
Despite the wide usage of parametric point processes in theory and applications, a sound goodness-of-fit procedure to test whether a given parametric model is appropriate for data coming from a self-exciting point processes has been missing in the literature. In this work, we establish a bootstrap-based goodness-of-fit test which empirically works for all kinds of self-exciting point processes (and even beyond). In an infill-asymptotic setting we also prove its asymptotic consistency, albeit only in the particular case that the underlying point process is inhomogeneous Poisson.
Cite
@article{arxiv.2407.09130,
title = {On goodness-of-fit testing for self-exciting point processes},
author = {José C. F. Kling and Mathias Vetter},
journal= {arXiv preprint arXiv:2407.09130},
year = {2024}
}