49 citations · 243 across the 39 of their papers we have counts for
43 papers
Compatibility of Space-Time Kernels with Full, Dynamical, or Compact Support
Tarik Faouzi, Reinhard Furrer, Emilio Porcu
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 o…
The Matérn Model: A Journey through Statistics, Numerical Analysis and Machine Learning
Emilio Porcu, Moreno Bevilacqua, Robert Schaback +1
The Matérn model has been a cornerstone of spatial statistics for more than half a century. More recently, the Matérn model has been central to disciplines as diverse as numerical…
Hybrid Parametric Classes of Isotropic Covariance Functions for Spatial Random Fields
Alfredo Alegría, Fabián Ramírez, Emilio Porcu
Covariance functions are the core of spatial statistics, stochastic processes, machine learning as well as many other theoretical and applied disciplines. The properties of the cov…
Sobolev Spaces, Kernels and Discrepancies over Hyperspheres
Simon Hubbert, Emilio Porcu, Chris. J. Oates +1
This work provides theoretical foundations for kernel methods in the hyperspherical context. Specifically, we characterise the native spaces (reproducing kernel Hilbert spaces) and…
Nonseparable Space-Time Stationary Covariance Functions on Networks cross Time
Emilio Porcu, Philip A. White, Marc G. Genton
The advent of data science has provided an increasing number of challenges with high data complexity. This paper addresses the challenge of space-time data where the spatial domain…
Convergence Arguments to Bridge Cauchy and Matérn Covariance Functions
Tarik Faouzi, Emilio Procu, Igor Kondrashuk +1
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 fa…