Brief Communication: Earthquake sequencing: analysis of time series constructed from the Markov chain model

Brief Communication: Earthquake sequencing: analysis of time series constructed from the Markov chain model

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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 jeep grand cherokee 5.7 turbo kit 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 modbiv 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.