Conference Papers

• A. Alegría, X. Emery, X. Freulon, C. Lantuéjoul, E. Porcu & D. Renard. Spectral Simulation of Gaussian Vector Random Fields on the Sphere. Geostatistics Toronto 2021. Springer Proceedings in Earth and Environmental Sciences

Publications in Journals

Submitted

• 29 A. Alegría, G. Cleanthous & A. Georgiadis. Series expansion and fast simulations of multivariate isotropic random fields on the paraboloid

• 28 T. Filosi, E. Porcu, X. Emery, C. Agostinelli & A. Alegría. Vector-Valued Gaussian Processes and their Kernels on a Class of Metric Graphs

• 27 A. Alegría, X. Emery, T. Filosi & E. Porcu. Computationally Efficient Algorithms for Simulating Isotropic Gaussian Random Fields on Graphs with Euclidean Edges (arxiv)

• 26 A. Alegría. Assessing the Competitiveness of Matrix-Free Block Likelihood Estimation in Spatial Models (arxiv)

Accepted/Published

• 25 A. Villazón, A. Alegría & X. Emery (2025). Neural Networks for Parameter Estimation in Geostatistical Models with Geometric Anisotropies. Machine Learning: Science and Technology, 6(2), 025025

• 24 A. Alegría & X. Emery (2026). Versatile Parametric Classes of Covariance Functions that Interlace Anisotropies and Hole Effects. Statistica Sinica (forthcoming)

• 23 A. Alegría, G. Cleanthous, A. Georgiadis, E. Porcu & P. White (2024). Gaussian Random Fields on the Product of Spheres: Theory and Applications. Electronic Journal of Statistics, 18(1), 1394-1435

• 22 A. Alegría & X. Emery (2024). Matrix-Valued Isotropic Covariance Functions with Local Extrema. Journal of Multivariate Analysis, 200, 105250

• 21 A. Alegría, F. Ramírez & E. Porcu (2024). Hybrid Parametric Classes of Isotropic Covariance Functions for Spatial Random Fields. Mathematical Geosciences, 56, 1517–1537 

• 20 A. Alegría (2023). Effective Sample Size for Georeferenced and Temporally Evolving Data. Spatial Statistics, 53, 100721

• 19 X. Emery & A. Alegría (2022). The Gauss Hypergeometric Covariance Kernel for Modeling Second-Order Stationary Random Fields in Euclidean Spaces: its Compact Support, Properties and Spectral Representation. Stochastic Environmental Research and Risk Assessment, 36(9), 2819-2834

• 18 X. Emery, A. Alegría & D. Arroyo (2021). Covariance models and simulation algorithm for stationary vector random fields on spheres crossed with Euclidean spaces. SIAM Journal on Scientific Computing, 43(5), A3114–A3134

• 17 J. Acosta, A. Alegría, F. Osorio & R. Vallejos (2021). Assessing the effective sample size for large spatial datasets: A block likelihood approach. Computational Statistics & Data Analysis, 162, 107282

• 16 A. Alegría, F. Cuevas, P. Diggle & E. Porcu (2021). The F family of covariance functions: A Matérn analogue for modeling random fields on spheres. Spatial Statistics, 43, 100512

• 15 A. Alegría, P.G. Bissiri, G. Cleanthous, E. Porcu & P. White (2021). Multivariate Isotropic Random Fields on Spheres: Nonparametric Bayesian Modeling and Lp Fast Approximations. Electronic Journal of Statistics, 15(1), 2360-2392

• 14 A. Alegría, X. Emery & E. Porcu (2021). Bivariate Matérn Covariances with Cross-Dimple for Modeling Coregionalized Variables. Spatial Statistics, 41, 100491

• 13 X. Emery & A. Alegría (2020). A spectral algorithm to simulate nonstationary random fields on spheres and multifractal star-shaped random sets. Stochastic Environmental Research and Risk Assessment, 34(12), 2301-2311

• 12 A. Alegría, X. Emery & C. Lantuéjoul (2020). The turning arcs: a computationally efficient algorithm to simulate isotropic vector-valued Gaussian random fields on the d-sphere. Statistics and Computing, 30(5), 1403-1418

• 11 A. Alegría & F. Cuevas (2020). Karhunen-Loève expansions for axially symmetric Gaussian processes: modeling strategies and L2 approximations. Stochastic Environmental Research and Risk Assessment, 34(11), 1953-1965

• 10 A. Alegría (2020). Cross-Dimple in the Cross-Covariance Functions of Bivariate Isotropic Random Fields on Spheres. Stat, 9(1):e301

• 9  E. Porcu, S. Castruccio, A. Alegría & P. Crippa (2019). Axially symmetric models for global data: A journey between geostatistics and stochastic generators​. Environmetrics, 30(1), e2555

• 8  A. Alegría, E. Porcu, R. Furrer & J. Mateu (2019). Covariance functions for multivariate Gaussian fields evolving temporally over planet Earth. Stochastic Environmental Research and Risk Assessment, 33(8), 1593-1608

• 7  J. Clarke, A. Alegría & E. Porcu (2018). Regularity properties and simulations of Gaussian random fields on the sphere cross time. Electronic Journal of Statistics, 12(1), 399-426

• 6  E. Porcu, A. Alegría & R. Furrer (2018). Modeling Temporally Evolving and Spatially Globally Dependent Data. International Statistical Review, 86(2), 344-377

• 5  A. Alegría, E. Porcu & R. Furrer (2018). Asymmetric Matrix-Valued Covariances for Multivariate Random Fields on Spheres. Journal of Statistical Computation and Simulation, 88(10), 1850-1862

• 4  A. Alegría & E. Porcu (2017). The dimple problem related to space-time modeling under the Lagrangian framework. Journal of Multivariate Analysis, 162, 110-121

• 3  A. Alegría, S. Caro, M. Bevilacqua, E. Porcu & J. Clarke (2017). Estimating covariance functions of multivariate skew-Gaussian random fields on the sphere. Spatial Statistics, 22, 388-402

• 2  A. Alegría, M. Bevilacqua & E. Porcu (2016). Likelihood-based inference for multivariate space-time wrapped-Gaussian fields. Journal of Statistical Computation and Simulation, 86(13), 2583-2597

• 1  M. Bevilacqua, A. Alegría, D. Velandia & E. Porcu (2016). Composite likelihood inference for multivariate Gaussian random fields. Journal of Agricultural Biological and Environmental Statistics, 21(3), 448-469