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The present research work is primarily carried out to select the suitable and better variants or functions of ETAS models to describe the energetic offshore earthquake swarms following 26 December 2004 (MW 9.1) and 21 March 2014 (MW 6.5) along the Andaman–Sumatra subduction zone. An attempt has also been made to inspect the variability of the selected model parameters from this robust estimation to discuss the physical mechanism differences between the SSE-related and fluid- or magma-related swarm sequences. For this purpose, different variants of ETAS models, such as single ETAS model, combined ETAS model, Boxcar swarm model, and exponential swarm model, are utilized for investigating the seismic anomalies by estimating the model parameters from the earthquake occurrence times using maximum likelihood method. The estimated AIC (Akaike information criterion) values for all these models suggest that the exponential swarm model outperforms the other models in successfully explaining the transient changes of background seismicity for the five energetic earthquake swarms triggered by the volcano-tectonic activities in the Andaman Sea. The reason is undoubtedly related to the localized nature of magmatic intrusion or fluid migration that caused the swarms and the exponential decay patterns of earthquakes after the initiation of the swarms. Although the swarms exhibit the shape of exponential function, the background seismicity shown by the parameter μ increases by one order during the swarm as compared to the pre-swarm period in the sub-catalogue. Therefore, the procedure of identifying improved variants or functions of ETAS models and estimating model parameters using earthquake occurrence times enhances our understanding of earthquake-triggering mechanisms, potential swarm activity patterns, and the intricate interplay between seismicity and volcanic processes in submarine volcanic arcs. While this approach might not facilitate real-time forecasting, it remains instrumental in characterizing seismic patterns and providing essential information for effective hazard assessment and the formulation of mitigation strategies within the coastal areas of the Andaman–Nicobar Islands region. [ABSTRACT FROM AUTHOR]

The statistically point process model known as epidemic-type aftershock sequence (ETAS) model is employed for systematically investigating the seismic quiescence or seismic anomalies around the focal regions of large/strong earthquakes for NW Himalaya. For this propose, the model predicted the expected occurrence rates of earthquakes by estimating the model parameters from the earthquake occurrences times using maximum likelihood method, has been used. Then the exhibited relative quiescence due to decreasing occurrence rates from the modeled ones can be identified by inspecting the abnormally downward deviated plot from the extended cumulative curve of the Residual Point Process (RPP) events. Examination of such RPP events in the whole time interval exhibits significant 1.5 years and 2.0 years of relative seismic quiescence before the strong 1991 Uttarkashi (MW 6.8) and 1999 Chamoli (MW 6.6) earthquakes, respectively. Considering the optimally oriented planes of Uttarkashi earthquake, the Coulomb stress changes (ΔCFS) have been investigated to check the rate of seismicity around the focal region of Chamoli earthquake. It has been found that ΔCFS of Uttarkashi earthquake exhibits stress shadow in or near the source zone of Chamoli earthquake and eventually decreases seismicity rates due to seismic quiescence in the source zone. On the other hand, the detected quiescence and activation relative to the predicted seismicity rate are consistent with the obtained Coulomb stress to depict the associated anomalies being sensitive enough to detect a slight stress change in the study region. Henceforth, the increased or decreased seismic activity due to seismic activation or quiescence is found to be consistent with the patterns of the Coulomb's stress changes calculated on the ruptured fault planes of Uttarkashi earthquake. Hence, this ETAS model based on statistical technique can thus be incorporated with other sensitive geophysical instruments for identifying seismically quiet period not only in the seismic gaps, but also in its neighborhoods along the Himalayan range for mitigating seismic hazards due to impending great earthquakes. [ABSTRACT FROM AUTHOR]