1 citations · 1 across the 2 of their papers we have counts for
3 papers
math.ST2026
Non-Stationary Covariance Functions for Spatial Data on Linear Networks
Alfredo AlegrÃa
We introduce a novel class of non-stationary covariance functions for random fields on linear networks that allows both the variance and the correlation range of the random field t…
stat.ME2026★ 1 cited
Effective Sample Size for Functional Spatial Data
Alfredo AlegrÃa, John Gómez, Jorge Mateu +1
The effective sample size quantifies the amount of independent information contained in a dataset, accounting for redundancy due to correlation between observations. While widely u…
stat.ME2024
Neural Networks for Parameter Estimation in Geometrically Anisotropic Geostatistical Models
Alejandro Villazón, Alfredo AlegrÃa, Xavier Emery
This article presents a neural network approach for estimating the covariance function of spatial Gaussian random fields defined in a portion of the Euclidean plane. Our proposal b…