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\begin{document}

\title{Statistics and Forecasting of Aftershocks during the 2019 Ridgecrest,
California, Earthquake Sequence}



\author[1,1]{Robert Shcherbakov}%
\affil[1]{Western University}%


\vspace{-1em}



  
  \date{June 14, 2024}


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\begin{abstract}
The 2019 Ridgecrest, California, earthquake sequence represents a
complex pattern of seismicity that is characterized by the occurrence of
a well defined foreshock sequence followed by a mainshock and subsequent
aftershocks. In this work, a detailed statistical analysis of the
sequence is performed. Particularly, the parametric modelling of the
frequency-magnitude statistics and the earthquake occurrence rate is
carried out. It is shown that the clustering of earthquakes plays an
important role during the evolution of this sequence. In addition, the
problem of constraining the magnitude of the largest expected
aftershocks to occur during the evolution of the sequence is addressed.
In order to do this, two approaches are considered. The first one is
based on the extreme value theory, whereas the second one uses the
Bayesian predictive framework. The latter approach has allowed to
incorporate the complex earthquake clustering through the Epidemic Type
Aftershock Sequence (ETAS) process and the uncertainties associated with
the model parameters into the computation of the corresponding
probabilities. The results indicate that the inclusion of the foreshock
sequence into the analysis produces higher probabilities for the
occurrence of the largest expected aftershocks after the M7.1 mainshock
compared to the approach based on the extreme value distribution
combined with the Omori-Utsu formula for the earthquake rate. Several
statistical tests are applied to verify the forecast.%
\end{abstract}%



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