Brief Communication: Earthquake sequencing: analysis of time series constructed from the Markov chain model
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...
Main Authors: | , |
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Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2015-10-01
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Series: | Nonlinear Processes in Geophysics |
Online Access: | http://www.nonlin-processes-geophys.net/22/589/2015/npg-22-589-2015.pdf |
Summary: | 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. |
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ISSN: | 1023-5809 1607-7946 |