Convergence arguments to bridge cauchy and matérn covariance functions
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 |