In this paper, we present a maximum likelihood method for estimating the parameters of a univariate Hawkes process with self-excitation or inhibition. Our work generalizes techniques and results that were restricted to the self-exciting scenario. The proposed estimator is implemented for the classical exponential kernel and we show that, in the inhibition context, our procedure provides more accurate estimations than current alternative approaches.

翻译：在本文中,我们提出一种最有可能的方法,用自我刺激或抑制来估计独一的霍克斯过程的参数。我们的工作概括了限于自我刺激情景的技术和结果。提议的估计值用于古典指数内核,我们表明,在抑制的情况下,我们的程序提供比目前替代方法更准确的估计值。