15 citations · 26 across the 6 of their papers we have counts for
10 papers
The Gauss Hypergeometric Covariance Kernel for Modeling Second-Order Stationary Random Fields in Euclidean Spaces: its Compact Support, Properties and Spectral Representation
Xavier Emery, Alfredo Alegría
This paper presents a parametric family of compactly-supported positive semidefinite kernels aimed to model the covariance structure of second-order stationary isotropic random fie…
The -family of covariance functions: A Matérn analogue for modeling random fields on spheres
Alfredo Alegría, Francisco Cuevas-Pacheco, Peter Diggle +1
The Mat{é}rn family of isotropic covariance functions has been central to the theoretical development and application of statistical models for geospatial data. For global data def…
Karhunen-Loève Expansions for Axially Symmetric Gaussian Processes: Modeling Strategies and Approximations
Alfredo Alegría, Francisco Cuevas-Pacheco
Axially symmetric processes on spheres, for which the second-order dependency structure may substantially vary with shifts in latitude, are a prominent alternative to model the spa…
The Turning Arcs: a Computationally Efficient Algorithm to Simulate Isotropic Vector-Valued Gaussian Random Fields on the -Sphere
Alfredo Alegría, Xavier Emery, Christian Lantuéjoul
Random fields on the sphere play a fundamental role in the natural sciences. This paper presents a simulation algorithm parenthetical to the spectral turning bands method used in E…
Modelling and simulation of multifractal star-shaped particles
Alfredo Alegría
The problem of constructing flexible stochastic models to describe the variability in shape of solid particles is challenging. Natural objects often exhibit mono- or multi-fractal…
Modeling Temporally Evolving and Spatially Globally Dependent Data
Emilio Porcu, Alfredo Alegría, Reinhard Furrer
The last decades have seen an unprecedented increase in the availability of data sets that are inherently global and temporally evolving, from remotely sensed networks to climate m…
Asymmetric Matrix-Valued Covariances for Multivariate Random Fields on Spheres
Alfredo Alegría, Emilio Porcu, Reinhard Furrer
Matrix-valued covariance functions are crucial to geostatistical modeling of multivariate spatial data. The classical assumption of symmetry of a multivariate covariance function i…
Space-Time Geostatistical Models with both Linear and Seasonal Structures in the Temporal Components
Alfredo Alegría, Emilio Porcu
We provide a novel approach to model space-time random fields where the temporal argument is decomposed into two parts. The former captures the linear argument, which is related, f…
Estimating covariance functions of multivariate skew-Gaussian random fields on the sphere
Alfredo Alegría, Sandra Caro, Moreno Bevilacqua +2
This paper considers a multivariate spatial random field, with each component having univariate marginal distributions of the skew-Gaussian type. We assume that the field is define…
Regularity properties and simulations of Gaussian random fields on the Sphere cross Time
Jorge Clarke de La Cerda, Alfredo Alegría, Emilio Porcu +1
We study the regularity properties of Gaussian fields defined over spheres cross time. In particular, we consider two alternative spectral decompositions for a Gaussian field on $\…