most citedA goodness-of-fit test for regression models with spatially correlated errors

8 citations · 14 across the 2 of their papers we have counts for

collaborators

5 papers

physics.flu-dyn2024

Actuation manifold from snapshot data

Luigi Marra, Guy Y. Cornejo Maceda, Andrea Meilán-Vila +5

We propose a data-driven methodology to learn a low-dimensional manifold of controlled flows. The starting point is resolving snapshot flow data for a representative ensemble of ac…

stat.ME20248 cited

A goodness-of-fit test for regression models with spatially correlated errors

Andrea Meilán-Vila, Jean D. Opsomer, Mario Francisco-Fernández +1

The problem of assessing a parametric regression model in the presence of spatial correlation is addressed in this work. For that purpose, a goodness-of-fit test based on a -d…

stat.ME20246 cited

Nonparametric estimation of circular trend surfaces with application to wave directions

Andrea Meilán-Vila, Rosa M. Crujeiras, Mario Francisco-Fernández

In oceanography, modeling wave fields requires the use of statistical tools capable of handling the circular nature of the {data measurements}. An important issue in ocean wave ana…

physics.flu-dyn2024

Self-tuning model predictive control for wake flows

Luigi Marra, Andrea Meilán-Vila, Stefano Discetti

This study presents a noise-robust closed-loop control strategy for wake flows employing model predictive control. The proposed control framework involves the autonomous offline se…

stat.ME2020

A computational validation for nonparametric assessment of spatial trends

Andrea Meilán-Vila, Rubén Fernández-Casal, Rosa M. Crujeiras Mario Francisco-Fernández

The analysis of continuously spatially varying processes usually considers two sources of variation, namely, the large-scale variation collected by the trend of the process, and th…