1,721,021 research outputs found

    Statistical analysis of the completeness of a seismic catalogue

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    Among the numerous issues that the study of seismic events presents, the incompleteness of catalogues is certainly one of the most important. It is also one that only the contribution of many and different skills can provide with a valid solution. In this paper the search for the complete part of a catalogue is expressed in terms of identification of the changepoint in a hierarchical Bayesian model. Stochastic simulation methods, recently presented in the literature, have enabled us to overcome the computational issues that previously made this approach prohibitive. We have applied the method on data, drawn from the Italian NT4.1.1 catalogue, related to some seismogenetic zones of ZS.4 zonation within which we assume spatial incompleteness to be homogeneous. The results obtained are given in the concluding sections of the paper

    Nonparametric Bayesian Estimation of Probability Density Function

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    Estimation of a probability density function based on parametric statistical mod- els can be highly imprecise and misleading when data are sparse and irregular. In these cases a semiparametric or nonparametric model is preferable and can better capture the data structure. We propose a Bayesian hierarchical model for the estimation of the probability density function. We use a Polya tree (Lavine 1992, 1994) as a nonparametric prior for a random probability measure. The binary partition of the Polya tree is obtained through the quantiles of a Generalized Gamma density function whose parameters are themselves Gamma-distributed random variables. The estimation technique is based on a MCMC sampler using Metropolis-Hastings within Gibbs sampling. We then apply the presented model to the interevent times between strong earthquakes which have occurred between 1600 and 1992 in Italy

    Bayesian analysis of the local intensity attenuation

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    We present a method that allows us to incorporate additional information from the historical earthquake felt reports in the probability estimation of local intensity attenuation. The approach is based on two ideas: a) standard intensity versus epicentral distance relationships constitute an unnecessary lter between observations and estimates; and b) the intensity decay process is a ected by many, scarcely known elements; hence intensity decay should be treated as a random variable as is the macroseismic intensity. The observations related to earthquakes with their epicenter outside the area concerned, but belonging to homogeneous zones, are used as prior knowledge of the phenomenon, while the data points of events inside the area are used to update the estimates through the posterior means of the quantities involved.Publishedope

    Bayesian analysis of the local intensity attenuation

    No full text
    We present a method that allows us to incorporate additional information from the historical earthquake felt reports in the probability estimation of local intensity attenuation. The approach is based on two ideas: a) standard intensity versus epicentral distance relationships constitute an unnecessary lter between observations and estimates; and b) the intensity decay process is a ected by many, scarcely known elements; hence intensity decay should be treated as a random variable as is the macroseismic intensity. The observations related to earthquakes with their epicenter outside the area concerned, but belonging to homogeneous zones, are used as prior knowledge of the phenomenon, while the data points of events inside the area are used to update the estimates through the posterior means of the quantities involved.Publishedope
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