English

Compatibility of Space-Time Kernels with Full, Dynamical, or Compact Support

Statistics Theory 2023-06-13 v1 Statistics Theory

Abstract

We deal with the comparison of space-time covariance kernels having, either, full, spatially dynamical, or space-time compact support. Such a comparison is based on compatibility of these covariance models under fixed domain asymptotics, having a theoretical background that is substantially coming from equivalence or orthogonality of Gaussian measures. In turn, such a theory is intimately related to the tails of the spectral densities associated with the three models. Models with space-time compact support are still elusive. We taper the temporal part of a model with dynamical support, obtaining a space-time compact support. The spectrum related to such a construction is obtained through temporal convolution of the spatially dynamical spectrum with the spectrum associated with the temporal taper. The solution of such a challenge opens the door to the compatibility-based comparison. Our findings show that indeed these three models can be compatible under some suitable parametric restrictions. As a corollary, we deduce implications in terms of maximum likelihood estimation and misspecified kriging prediction under fixed domain asymptotics.

Keywords

Cite

@article{arxiv.2306.06829,
  title  = {Compatibility of Space-Time Kernels with Full, Dynamical, or Compact Support},
  author = {Tarik Faouzi and Reinhard Furrer and Emilio Porcu},
  journal= {arXiv preprint arXiv:2306.06829},
  year   = {2023}
}

Comments

28 pages

R2 v1 2026-06-28T11:02:30.980Z