Convergence arguments to bridge cauchy and matérn covariance functions

Faouzi; T.; Porcu; E.; Kondrashuk; I.; Bevilacqua; M.

Abstract

The Matérn and the Generalized Cauchy families of covariance functions have a prominent role in spatial statistics as well as in a wealth of statistical applications. The Matérn family is crucial to index mean-square differentiability of the associated Gaussian random field; the Cauchy family is a decoupler of the fractal dimension and Hurst effect for Gaussian random fields that are not self-similar. Our effort is devoted to prove that a scale-dependent family of covariance functions, obtained as a reparameterization of the Generalized Cauchy family, converges to a particular case of the Matérn family, providing a somewhat surprising bridge between covariance models with light tails and covariance models that allow for long memory effect. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023.

Más información

Título según WOS: Convergence arguments to bridge cauchy and matern covariance functions
Título según SCOPUS: Convergence arguments to bridge cauchy and matérn covariance functions
Título de la Revista: Statistical Papers
Volumen: 65
Número: 2
Editorial: Springer Science and Business Media Deutschland GmbH
Fecha de publicación: 2024
Página de inicio: 645
Página final: 660
Idioma: English
DOI:

10.1007/s00362-023-01400-9

Notas: ISI, SCOPUS