Search results for "Point Process"
showing 10 items of 102 documents
Fitting and Testing Point Process Models
2008
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…
Kernel intensity for space-time point processes with application to seismological problems
2010
Dealing with data coming from a space-time inhomogeneous process, there is often the need of semi-parametric estimates of the conditional intensity function; isotropic or anisotropic multivariate kernel estimates can be used, with windows sizes h. The properties of the intensities estimated with this choice of h are not always good for specific fields of application; we could try to choose h in order to have good predictive properties of the estimated intensity function. Since a direct ML approach cannot be followed, we propose an estimation procedure, computationally intensive, based on the subsequent increments of likelihood obtained adding an observation at time. The first results obtain…
Comparing estimators of the galaxy correlation function
1999
We present a systematic comparison of some usual estimators of the 2--point correlation function, some of them currently used in Cosmology, others extensively employed in the field of the statistical analysis of point processes. At small scales, it is known that the correlation function follows reasonably well a power--law expression $\xi(r) \propto r^{-\gamma}$. The accurate determination of the exponent $\gamma$ (the order of the pole) depends on the estimator used for $\xi(r)$; on the other hand, its behavior at large scale gives information on a possible trend to homogeneity. We study the concept, the possible bias, the dependence on random samples and the errors of each estimator. Erro…
Statistics of Galaxy Clustering
2006
In this introductory talk we will establish connections between the statistical analysis of galaxy clustering in cosmology and recent work in mainstream spatial statistics. The lecture will review the methods of spatial statistics used by both sets of scholars, having in mind the cross-fertilizing purpose of the meeting series. Special topics will be: description of the galaxy samples, selection effects and biases, correlation functions, nearest neighbor distances, void probability functions, Fourier analysis, and structure statistics.
Space-time Point Processes semi-parametric estimation with predictive measure information
2014
In this paper, we provide a method to estimate the space-time intensity of a branching-type point process by mixing nonparametric and parametric approaches. The method accounts simultaneously for the estimation of the different model components, applying a forward predictive likelihood estimation approach to semi-parametric models.
Diagnostics for nonparametric estimation in space-time seismic processes
2010
In this paper we propose a nonparametric method, based on locally variable bandwidths kernel estimators, to describe the space-time variation of seismic activity of a region of Southern California. The flexible estimation approach is introduced together with a diagnostic method for space-time point process, based on the interpretation of some second-order statistics, to analyze the dependence structure of observed data and suggest directions for fit improvement. In this paper we review a diagnostic method for space-time point processes based on the interpretation of the transformed version of some second-order statistics. The method is useful to analyze dependence structures of observed dat…
Procesos puntuales como herramienta para el análisis de posibles fuentes de contaminación
2002
El análisis de un patrón puntual engloba una serie de técnicas que permiten estudiar la distribución de un conjunto de eventos ocurridos sobre una región del plano. Este problema surge en epidemiología cuando se investiga una potencial fuente de contaminación ambiental alrededor de la cual se sospecha que surgen casos de una determinada enfermedad. En el presente trabajo, se explica brevemente en qué consiste el análisis de un patrón puntual y se ilustra con una aplicación a la determinación del origen medioambiental y al estudio de las zonas de mayor riesgo de incidencia en un brote de neumonía por Legionella ocurrido entre mediados de septiembre y principios de octubre en la ciudad de Alc…
Non-Periodic Systems with Continuous Diffraction Measures
2015
The present state of mathematical diffraction theory for systems with continuous spectral components is reviewed and extended. We begin with a discussion of various characteristic examples with singular or absolutely continuous diffraction, and then continue with a more general exposition of a systematic approach via stationary stochastic point processes. Here, the intensity measure of the Palm measure takes the role of the autocorrelation measure in the traditional approach. We furthermore introduce a ‘Palm-type’ measure for general complex-valued random measures that are stationary and ergodic, and relate its intensity measure to the autocorrelation measure.
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.