Search results for " spatio-temporal point processes"

showing 5 items of 5 documents

Minimum contrast for point processes' first-order intensity estimation

2023

In this paper, we exploit some theoretical results, from which we know the expected value of the K-function weighted by the true first-order intensity function of a point pattern. This theoretical result can serve as an estimation method for obtaining the parameter estimates of a specific model, assumed for the data. The only requirement is the knowledge of the first-order intensity function expression, completely avoiding writing the likelihood, which is often complex to deal with in point process models. We illustrate the method through simulation studies for spatio-temporal point processes.

Second-order characteristics Spatial statistics Spatio-temporal point processes Local models Minimum contrastSettore SECS-S/01 - Statistica
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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 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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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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Community detection of seismic point processes

2022

In this paper, we combine robin and Local Indicators of Spatio-Temporal Association (LISTA) functions. robin is an R package to assess the robustness of the community structure of a network found by one or more methods to give indications about their reliability. We use it to propose a classification algorithm of events in a spatio-temporal point pattern, by means of the local second-order characteristics and the community detection procedure in network analysis. We demonstrate the proposed procedure on a real data analysis on seismic data.

network analysis community detection algorithm second-order characteristics spatio-temporal point processes statistical validation earthquakesSettore SECS-S/01 - Statistica
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