Search results for "log-Gaussian Cox proce"

showing 10 items of 10 documents

Joint second-order parameter estimation for spatio-temporal log-Gaussian Cox processes

2018

We propose a new fitting method to estimate the set of second-order parameters for the class of homogeneous spatio-temporal log-Gaussian Cox point processes. With simulations, we show that the proposed minimum contrast procedure, based on the spatio-temporal pair correlation function, provides reliable estimates and we compare the results with the current available methods. Moreover, the proposed method can be used in the case of both separable and non-separable parametric specifications of the correlation function of the underlying Gaussian Random Field. We describe earthquake sequences comparing several Cox model specifications.

spatio-temporal pair correlation functionEnvironmental EngineeringGaussianminimum contrast methodnon-separable covariance function010502 geochemistry & geophysics01 natural sciencesPoint processGaussian random fieldSet (abstract data type)010104 statistics & probabilitysymbols.namesakeCorrelation functionEnvironmental Chemistry0101 mathematicsSafety Risk Reliability and Qualityearthquakes0105 earth and related environmental sciencesGeneral Environmental ScienceWater Science and TechnologyParametric statisticsMathematicslog-Gaussian Cox processesEstimation theoryContrast (statistics)symbolsEarthquakes Log-Gaussian Cox processes Minimum contrast method Non-separable covariance function Spatio-temporal pair correlation functionSettore SECS-S/01 - StatisticaAlgorithm
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Models and methods for space and space-time interactions in complex point processes with applications on earthquakes

spatial covariatespatial point processeearthquakes; hybrids of Gibbs point processes; spatial covariates; spatial point processes; hypothesis testing; local indicators of spatio-temporal association; permutation-based tests; second-order product density function; log-Gaussian Cox process; spatial anisotropy; spatio-temporal point process; clustering detectionlog-Gaussian Cox proceearthquakehybrids of Gibbs point processehypothesis testinglocal indicators of spatio-temporal associationpermutation-based testspatial anisotropysecond-order product density functionspatio-temporal point proceSettore SECS-S/01 - Statisticaclustering detection
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Inhomogeneous spatio-temporal point processes on linear networks for visitors’ stops data

2022

We analyse the spatio-temporal distribution of visitors' stops by touristic attractions in Palermo (Italy) using theory of stochastic point processes living on linear networks. We first propose an inhomogeneous Poisson point process model, with a separable parametric spatio-temporal first-order intensity. We account for the spatial interaction among points on the given network, fitting a Gibbs point process model with mixed effects for the purely spatial component. This allows us to study first-order and second-order properties of the point pattern, accounting both for the spatio-temporal clustering and interaction and for the spatio-temporal scale at which they operate. Due to the strong d…

Statistics and ProbabilityLog-Gaussian Cox processeSpatio-temporal point processesIntensity estimationGlobal Positioning SystemModeling and SimulationGibbs point processeLinear networkStatistics Probability and UncertaintySettore SECS-S/01 - StatisticaThe Annals of Applied Statistics
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Local Spatio-Temporal Log-Gaussian Cox Processes for seismic data analysis

2022

We propose a local version of the spatio-temporal log-Gaussian Cox processes (LGCPs) employing the Local Indicators of Spatio-Temporal Association (LISTA) functions into the minimum contrast procedure to obtain space as well as time-varying parameters. We resort to the joint minimum contrast method fitting method to estimate the set of second-order parameters for the class of Spatio-Temporal LGCPs. We employ the proposed methodology to analyse real seismic data occurred Greece between 2004 and 2015.

Earthquakes Second-order characteristics Spatio-temporal point processes Local models Log-Gaussian Cox Processes Minimum contrastSettore SECS-S/01 - Statistica
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Locally weighted spatio-temporal minimum contrast for Log-Gaussian Cox Processes

2022

We propose a local version of the spatio-temporal log-Gaussian Cox processes (LGCPs) employing the Local Indicators of Spatio-Temporal Association (LISTA) functions into the minimum contrast procedure to obtain space as well as time-varying parameters. We resort to the joint minimum contrast method fitting method to estimate the set of second-order parameters for the class of spatio-temporal LGCPs. This approach has the advantage of being usable in the case of both separable and non-separable parametric specifications of the correlation function of the underlying Gaussian Random Field (GRF).

Spatio-temporal point processeSecond-order characteristicsLog-Gaussian Cox ProcesseLocal modelSettore SECS-S/01 - StatisticaMinimum contrast
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Locally weighted minimum contrast estimation for spatio-temporal log-Gaussian Cox processes

2023

A local version of spatio-temporal log-Gaussian Cox processes is proposed by using Local Indicators of Spatio-Temporal Association (LISTA) functions plugged into the minimum contrast procedure, to obtain space as well as time-varying parameters. The new procedure resorts to the joint minimum contrast fitting method to estimate the set of second-order parameters. This approach has the advantage of being suitable in both separable and non-separable parametric specifications of the correlation function of the underlying Gaussian Random Field. Simulation studies to assess the performance of the proposed fitting procedure are presented, and an application to seismic spatio-temporal point pattern…

Methodology (stat.ME)FOS: Computer and information sciencesLocal models log-Gaussian Cox processes Minimum contrast Second-order characteristics Spatio-temporal point processesStatistics and ProbabilityComputational MathematicsComputational Theory and MathematicsApplied MathematicsSettore SECS-S/01 - StatisticaStatistics - ComputationStatistics - MethodologyComputation (stat.CO)Computational Statistics & Data Analysis
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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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Spatio-Temporal Linear Network Point Processes for GPS Data Analysis

This work aims at analyzing the spatio-temporal intensity in the distribution of stop locations of cruise passengers during their visit at the destination. Data are collected through the integration of GPS tracking technology and questionnaire-based survey on a sample of cruise passengers visiting the city of Palermo (Italy), and they are used to identify the main determinants which characterize cruise passengers’ stop locations pattern. The spatio-temporal distribution of visitors' stops is analysed by mean of the theory of stochastic point processes occurring on linear networks, in order to consider the street configuration of the city and the location of the main attractions. First, an i…

Gibbs point processes Intensity estimation Linear networks Log-Gaussian Cox Processes Spatio-temporal point processesSettore SECS-S/01 - Statistica
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Advanced spatio-temporal point processes for the Sicily seismicity analysis

2018

Due to the complexity of the generator process of seismic events, we study under several aspects the interaction structure between earthquake events using recently developed spatio-temporal statistical techniques and models. Using these advanced statistical tools, we aim to characterise the global and local scale cluster behaviour of the Easter Sicily seismicity considering the catalogue data since 2006, when the Italian National Seismic Network was upgraded and earthquake location was sensibly improved. Firstly, we characterise the global complex spatiotemporal interaction structure with the space-time ETAS model where background seismicity is estimated non-parametrically, while triggered …

earthquakelog-Gaussian Cox processespatiotemporal pair correlation functionminimum contrast methodhybrid of Gibbs procenon-separable covariance functionpoint proce
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Spatio-temporal log-Gaussian Cox processes on earthquake events

2016

This work presents an application of spatio-temporal log-Gaussian Cox processes for the description of earthquake events. To explain the overall spatial trend, spatial geological information in the study area such as faults and volcanoes are introduced in the model. Moreover, an anisotropic specification of the covariance matrix of the Gaussian process is used to improve the explanation of the phenomenon. We apply and compare different models to explain the seismic events occurred in Alaska over the last decades.

Earthquake datalog-Gaussian Cox processesAnisotropy; Earthquake data; log-Gaussian Cox processesAnisotropySettore SECS-S/01 - Statistica
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