Convergence arguments to bridge cauchy and matern covariance functions
Abstract
The Matern 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 Matern 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 Matern family, providing a somewhat surprising bridge between covariance models with light tails and covariance models that allow for long memory effect.
Más información
Título según WOS: | Convergence arguments to bridge cauchy and matern covariance functions |
Título de la Revista: | STATISTICAL PAPERS |
Editorial: | Springer |
Fecha de publicación: | 2023 |
DOI: |
10.1007/s00362-023-01400-9 |
Notas: | ISI |