Hawkes process is one of the most commonly used models for investigating the
self-exciting nature of earthquake occurrences. However, seismicity patterns
have complicated characteristics due to heterogeneous geology and stresses, for
which existing methods with Hawkes process cannot fully capture. This study
introduces novel nonparametric Hawkes process models that are flexible in three
distinct ways. First, we incorporate the spatial inhomogeneity of the
self-excitation earthquake productivity. Second, we consider the anisotropy in
aftershock occurrences. Third, we reflect the space-time interactions between
aftershocks with a non-separable spatio-temporal triggering structure. For
model estimation, we extend the model-independent stochastic declustering
(MISD) algorithm and suggest substituting its histogram-based estimators with
kernel methods. We demonstrate the utility of the proposed methods by applying
them to the seismicity data in regions with active seismic activities.Comment: 53 page