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Accelerating maximum likelihood estimation for Hawkes point processes
2013
2013 23rd International Conference on Field programmable Logic and Applications
Hawkes processes are point processes that can be used to build probabilistic models to describe and predict occurrence patterns of random events. They are widely used in highfrequency trading, seismic analysis and neuroscience. A critical numerical calculation in Hawkes process models is parameter estimation, which is used to fit a Hawkes process model to a data set. The parameter estimation problem can be solved by searching for a parameter set that maximises the log-likelihood. A core
doi:10.1109/fpl.2013.6645502
dblp:conf/fpl/GuoL13
fatcat:ffixiig7rrgn3lz6aczgfaydpq