4 citations · 4 across the 6 of their papers we have counts for
6 papers
Time-adaptive infinite-dimensional Gaussian process regression on manifolds
MD Ruiz-Medina, AE Madrid, A Torres-Signes +1
This paper proposes a new formulation of functional Gaussian Process regression on manifolds, based on an Empirical Bayes approach, in the spatiotemporal random field context. We a…
Local Fréchet functional regression in manifolds from time-correlated bivariate curve data
M. D. Ruiz-Medina, A. Torres-Signes
Under mild conditions, a least-squares local linear Fréchet curve predictor is derived for a response and a regressor evaluated in a separable Hilbert space. The conditions that al…
Global Fréchet regression from time correlated bivariate curve data in manifolds
A. Torres-Signes, M. P. Frías, M. D. Ruiz-Medina
Global Fréchet regression is addressed from the observation of a strictly stationary bivariate curve process, evaluated in a finite--dimensional compact differentiable Riemannian m…
A spatial functional count model for heterogeneity analysis in time
Torres-Signes, M. P. Frías, J. Mateu +1
A spatial curve dynamical model framework is adopted for functional prediction of counts in a spatiotemporal log-Gaussian Cox process model. Our spatial functional estimation appro…
COVID-19 mortality analysis from soft-data multivariate curve regression and machine learning
A. Torres-Signes, M. P. Frías, M. D. Ruiz-Medina
A multiple objective space-time forecasting approach is presented involving cyclical curve log-regression, and multivariate time series spatial residual correlation analysis. Speci…
Spatial Cox processes in an infinite-dimensional framework
M. P. Frías, A. Torres-Signes, M. D. Ruiz-Medina +1
We introduce a new class of spatial Cox processes driven by a Hilbert--valued random log--intensity. We adopt a parametric framework in the spectral domain, to estimate its spatial…