Search results for "local composite likelihood"

showing 2 items of 2 documents

Local Spatial Log-Gaussian Cox Processes for seismic data

2022

AbstractIn this paper, we propose the use of advanced and flexible statistical models to describe the spatial displacement of earthquake data. The paper aims to account for the external geological information in the description of complex seismic point processes, through the estimation of models with space varying parameters. A local version of the Log-Gaussian Cox processes (LGCP) is introduced and applied for the first time, exploiting the inferential tools in Baddeley (Spat Stat 22:261–295, 2017), estimating the model by the local Palm likelihood. We provide methods and approaches accounting for the interaction among points, typically described by LGCP models through the estimation of th…

Statistics and ProbabilityEconomics and Econometricsspatial point processeApplied MathematicsModeling and SimulationLog-Gaussian Cox procelocal composite likelihoodPalm likelihoodseismologySettore SECS-S/01 - StatisticaSocial Sciences (miscellaneous)Analysis
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Local LGCP estimation for spatial seismic processes

2020

Using recent results for local composite likelihood for spatial point processes, we show the performance of advanced and flexible statistical models to describe the spatial displacement of earthquake data. Local models described by Baddeley (2017) allow for the possibility of describing both seismic catalogs and sequences. When analysing seismic sequences, the analysis of the small scale variation is the main issue. The interaction among points is taken into account by Log-Gaussian Cox Processes models through the estimation of the parameters of the covariance of the Gaussian Random Field. In their local version these parameters are allowed to vary spatially, and this is a crucial aspect fo…

earthquakeGibbs proceCox procelocal composite likelihoodSettore SECS-S/01 - Statisticapoint process
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