4 papers
Computationally Efficient Algorithms for Simulating Isotropic Gaussian Random Fields on Graphs with Euclidean Edges
Alfredo Alegría, Xavier Emery, Tobia Filosi +1
This work addresses the problem of simulating Gaussian random fields that are continuously indexed over a class of metric graphs, termed graphs with Euclidean edges, being more gen…
Assessing the Impact of Block Size on Block Likelihood Estimation: A Comparative Study
Alfredo Alegría
This paper focuses on block likelihood estimation for geostatistical data, a method that balances statistical accuracy and computational efficiency. Central to this approach is the…
Versatile Parametric Classes of Covariance Functions that Interlace Anisotropies and Hole Effects
Alfredo Alegría, Xavier Emery
Covariance functions are a fundamental tool for modeling the dependence structure of spatial processes. This work investigates novel constructions for covariance functions that ena…
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…