Listar INIT_Articles por autoría "87aa6215-0879-41f2-bcc0-cbcaa996ac15"
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Covariance functions for multivariate Gaussian fields evolving temporally over planet earth
Alegría, Alfredo; Porcu, Emilio; Furrer, Reinhard; Mateu, Jorge Springer-Verlag GmbH Germany, part of Springer Nature (2019-07-18)The construction of valid and flexible cross-covariance functions is a fundamental task for modeling multivariate space– time data arising from, e.g., climatological and oceanographical phenomena. Indeed, a suitable ... -
Equivalence and orthogonality of Gaussian measures on spheres
Arafat, Ahmed; Porcu, Emilio; Bevilacqua, M.; Mateu, Jorge Elsevier (2018-09)The equivalence of Gaussian measures is a fundamental tool to establish the asymptotic properties of both prediction and estimation of Gaussian fields under fixed domain asymptotics. The paper solves Problem 18 in the list ... -
Estimating Space and Space-Time Covariance Functions for Large Data Sets: A Weighted Composite Likelihood Approach
Bevilacqua, M.; Gaetan, Carlo; Mateu, Jorge; Porcu, Emilio American Statistical Association (2012)In the last years there has been a growing interest in the construction space-time covariance functions. However, effective estimation methods for these models are some- how unexplored. In this paper we propose a composite ... -
Models of covariance functions of gaussian random fields escaping from isotropy, stationarity and non negativity
Gregori, Pablo; Porcu, Emilio; Mateu, Jorge International Society for Stereology (2014-01)This paper represents a survey of recent advances in modeling of space or space-time Gaussian Random Fields (GRF), tools of Geostatistics at hand for the understanding of special cases of noise in image analysis. They can ... -
Multivariate Kalman filtering for spatio-temporal processes
Ferreira, Guillermo; Mateu, Jorge; Porcu, Emilio Springer (2022)An increasing interest in models for multivariate spatio-temporal processes has been noted in the last years. Some of these models are very flexible and can capture both marginal and cross spatial associations amongst the ... -
New classes of spectral densities for lattice processes and random fields built from simple univariate margins
Porcu, Emilio; Mateu, Jorge; Gregori, Pablo; Ostoja-Starzewski, Martin Springer-Verlag (2012-05)Quasi arithmetic and Archimedean functionals are used to build new classes of spectral densities for processes defined on any d-dimensional lattice Zd and random fields defined on the d-dimensional Euclidean space Rd , ... -
Space-time autoregressive estimation and prediction with missing data based on Kalman filtering
Padilla-Solis, Leonardo Fabricio; Lagos Álvarez, Bernardo M.; Mateu, Jorge; Porcu, Emilio Wiley (2020-11)We propose a Kalman filter algorithm to provide a formal statistical analysis of space‐time data with an autoregressive structure in time. The Kalman filter technique allows to capture the temporal dependence as well as ... -
Spatio-temporal analysis with short- and long-memory dependence: a state-space approach
Ferreira, Guillermo; Mateu, Jorge; Porcu, Emilio Springer Berlin Heidelberg (2018)This paper deals with the estimation and prediction problems of spatio-temporal processes by using state-space methodology. The spatio-temporal process is represented through an infinite moving average decomposition. This ...