Maximum Likelihood Estimation

Patrick J. Laub, Young Lee and Thomas Taimre
Additional contact information
Patrick J. Laub: University of Melbourne, Faculty of Business and Economics
Young Lee: Harvard University, Faculty of Arts and Sciences
Thomas Taimre: The University of Queensland, School of Mathematics and Physics

Chapter Chapter 5 in The Elements of Hawkes Processes, 2021, pp 37-43 from Springer

Abstract: Abstract We now turn to the problem of fitting Hawkes processes to real-world data. The following chapters discuss Hawkes processes and how they fit into the common frameworks for statistical inference: maximum likelihood estimation, moment matching, the EM algorithm, and the Bayesian inference. The performance of these inference methods depends upon the excitation function μ(⋅) chosen and the number of observations there are to fit.

Date: 2021
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DOI: 10.1007/978-3-030-84639-8_5

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