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@article{Shlomovich:2022:10.1007/s11222-022-10121-2,
author = {Shlomovich, L and Cohen, E and Adams, N},
doi = {10.1007/s11222-022-10121-2},
journal = {Statistics and Computing},
title = {A parameter estimation method for multivariate binned Hawkes processes},
url = {http://dx.doi.org/10.1007/s11222-022-10121-2},
volume = {32},
year = {2022}
}

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TY  - JOUR
AB  - It is often assumed that events cannot occur simultaneously when modelling data with pointprocesses. This raises a problem as real-world dataoften contains synchronous observations due to aggregation or rounding, resulting from limitations onrecording capabilities and the expense of storing highvolumes of precise data. In order to gain a better understanding of the relationships between processes,we consider modelling the aggregated event data using multivariate Hawkes processes, which offer a description of mutually-exciting behaviour and havefound wide applications in areas including seismology and finance. Here we generalise existing methodology on parameter estimation of univariate aggregated Hawkes processes to the multivariate case using a Monte Carlo Expectation-Maximization (MCEM) algorithm and through a simulation study illustrate that alternative approaches to this problemcan be severely biased, with the multivariate MCEM method outperforming them in terms of MSE inall considered cases.
AU  - Shlomovich,L
AU  - Cohen,E
AU  - Adams,N
DO  - 10.1007/s11222-022-10121-2
PY  - 2022///
SN  - 0960-3174
TI  - A parameter estimation method for multivariate binned Hawkes processes
T2  - Statistics and Computing
UR  - http://dx.doi.org/10.1007/s11222-022-10121-2
UR  - http://hdl.handle.net/10044/1/97479
VL  - 32
ER  -

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