Measuring seismicity diversity and anomalies using point process models: case studies before and after the 2016 Kumamoto earthquakes in Kyushu, Japan

Earth, Planets and Space

Table 5 The MLEs of the single and two-stage ETAS models estimated for Regions A and B in Fig. 4

	Target period	\(\mu \left( { \times \,10^{ - 3} } \right)\)	\(K_{0}\)	\(c\left( { \times \,10^{ - 3} } \right)\)	\(\alpha\)	\(p\)	ΔAIC
Kumamoto Region A M _c = 2.0	S = 0.01, T _end = 9527.00	7.351	5.640	3.280	2.632	1.051	− 3.688
	S = 0.01, T _c = 5161.43	9.261	6.219	3.507	2.746	1.032
	T _c = 5161.43, T _end = 9105	8.016	0.050	3.732	2.077	2.059
Kumamoto Region B M _c = 2.0	S = 0.01, T _end = 4891.52	0.4950	5.281	2.233	2.738	1.081	− 3.551
	S = 0.01, T _c = 119.32	1.279	3.920	3.822	2.564	1.185
	T _c = 119.32, T _end = 4891.52	0.6071	2.935	1.311	29.20	0.951

The datasets start at 00:00 on January 1, 1990, and at 10:53 on June 8, 2000 (the occurrence time of a M5.0 event), for Regions A and B, respectively. For each region, the first row shows the MLE estimates of the parameters for the entire period (S, T _end) with the associated baseline AIC = AIC₀. The second row for the target period until the change-point (S, T _c) is associated with AIC = AIC₁, and the third row for the target period after the change-point (T _c, T _end) is associated with AIC = AIC₂. The last column shows ΔAIC = AIC₁ + AIC₂ − AIC₀