  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.
