Field and reverse field solitons in wave-operator nonlinear Schrödinger equation with space-time reverse: Modulation instability

HI Abdel-Gawad - Communications in Theoretical Physics, 2023 - iopscience.iop.org
The wave-operator nonlinear Schrödinger equation was introduced in the literature. Further,
nonlocal space–time reverse complex field equations were also recently introduced. Studies …

[HTML][HTML] The dimple problem related to space–time modeling under the Lagrangian framework

A Alegría, E Porcu - Journal of Multivariate Analysis, 2017 - Elsevier
Abstract Space–time covariance modeling under the Lagrangian framework has been
especially popular to study atmospheric phenomena in the presence of transport effects …

Bivariate Matérn covariances with cross-dimple for modeling coregionalized variables

A Alegría, X Emery, E Porcu - Spatial Statistics, 2021 - Elsevier
Modeling the spatial correlation structure of coregionalized data is a frequent task in
numerous fields of the natural sciences. Even in the isotropic case, experimental …

Contours and dimple for the Gneiting class of space-time correlation functions

F Cuevas, E Porcu, M Bevilacqua - Biometrika, 2017 - academic.oup.com
We offer a dual view of the dimple problem related to space-time correlation functions in
terms of their contours. We find that the dimple property in the Gneiting class of correlations …

Cross‐dimple in the cross‐covariance functions of bivariate isotropic random fields on spheres

A Alegría - Stat, 2020 - Wiley Online Library
Multivariate random fields allow to simultaneously model multiple spatially indexed
variables, playing a fundamental role in geophysical, environmental, and climate disciplines …

On the frequency domain composite likelihood methods for estimating space-time covariance functions for large datasets

AM Mosammam - Communications in Statistics-Simulation and …, 2023 - Taylor & Francis
Covariance function plays very important roles in modeling and in prediction of spatial data.
For instance, many statistical inferences such as maximum likelihood estimation and best …

Half spectral composite likelihood approach for estimating spatial–temporal covariance functions

AM Mosammam - Spatial Statistics, 2016 - Elsevier
In this paper we propose a method called half spectral composite likelihood for the
estimation of spatial–temporal covariance functions which involves a spectral approach in …

Spatial-depth functional estimation of ocean temperature from non-separable covariance models

RM Espejo, R Fernández-Pascual… - … Research and Risk …, 2017 - Springer
Spatial-depth functional regression is applied for the estimation of ocean temperature, with
projection onto the eigenvectors of the empirical covariance operator of the functional …

[引用][C] Spatial Statistics

A Alegría, X Emery, E Porcu - 2021

[引用][C] Cross-Dimple for Bivariate Isotropic Random Fields on Spheres

A Alegrıa - 2020