189 citations · 522 across the 27 of their papers we have counts for
5 papers · 1 filter
Nonparametric Spectral Methods for Multivariate Spatial and Spatial-Temporal Data
Joseph Guinness
We propose computationally efficient methods for estimating stationary multivariate spatial and spatial-temporal spectra from incomplete gridded data. The methods are iterative and…
Non-Stationary Covariance Estimation using the Stochastic Score Approximation for Large Spatial Data
Amanda Muyskens, Joseph Guinness, Montserrat Fuentes
We introduce computational methods that allow for effective estimation of a flexible, parametric non-stationary spatial model when the field size is too large to compute the multiv…
Multivariate Spatial-Temporal Variable Selection with Applications to Seasonal Tropical Cyclone Modeling
Marcela Alfaro Córdoba, Montserrat Fuentes, Joseph Guinness +1
Tropical cyclone and sea surface temperature data have been used in several studies to forecast the total number of hurricanes in the Atlantic Basin. Sea surface temperature (SST)…
Vecchia approximations of Gaussian-process predictions
Matthias Katzfuss, Joseph Guinness, Wenlong Gong +1
Gaussian processes (GPs) are highly flexible function estimators used for geospatial analysis, nonparametric regression, and machine learning, but they are computationally infeasib…
Spatial shrinkage via the product independent Gaussian process prior
Arkaprava Roy, Brian J. Reich, Joseph Guinness +2
We study the problem of sparse signal detection on a spatial domain. We propose a novel approach to model continuous signals that are sparse and piecewise smooth as product of inde…