brief communication: earthquake sequencing: analysis of time series constructed from the markov chain model

Clicks: 162
ID: 152198
2015
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Abstract
Directed graph representation of a Markov chain model to study global earthquake sequencing leads to a time series of state-to-state transition probabilities that includes the spatio-temporally linked recurrent events in the record-breaking sense. A state refers to a configuration comprised of zones with either the occurrence or non-occurrence of an earthquake in each zone in a pre-determined time interval. Since the time series is derived from non-linear and non-stationary earthquake sequencing, we use known analysis methods to glean new information. We apply decomposition procedures such as ensemble empirical mode decomposition (EEMD) to study the state-to-state fluctuations in each of the intrinsic mode functions. We subject the intrinsic mode functions, derived from the time series using the EEMD, to a detailed analysis to draw information content of the time series. Also, we investigate the influence of random noise on the data-driven state-to-state transition probabilities. We consider a second aspect of earthquake sequencing that is closely tied to its time-correlative behaviour. Here, we extend the Fano factor and Allan factor analysis to the time series of state-to-state transition frequencies of a Markov chain. Our results support not only the usefulness of the intrinsic mode functions in understanding the time series but also the presence of power-law behaviour exemplified by the Fano factor and the Allan factor.
Reference Key
cavers2015nonlinearbrief Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;M. S. Cavers;K. Vasudevan
Journal BMC research notes
Year 2015
DOI
10.5194/npg-22-589-2015
URL
http://www.nonlin-processes-geophys.net/22/589/2015/npg-22-589-2015.pdf
Keywords
cosmic physics sciencephysicsgeophysics

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