189 citations · 522 across the 27 of their papers we have counts for
6 papers · 1 filter
Inverses of Matern Covariances on Grids
Joseph Guinness
We conduct a study of the aliased spectral densities of Matérn covariance functions on a regular grid of points, providing clarity on the properties of a popular approximation base…
Mean-dependent nonstationary spatial models
Geoffrey Colin Lee Peterson, Joseph Guinness, Adam Terando +1
Nonstationarity is a major challenge in analyzing spatial data. For example, daily precipitation measurements may have increased variability and decreased spatial smoothness in are…
Gaussian Process Learning via Fisher Scoring of Vecchia's Approximation
Joseph Guinness
We derive a single pass algorithm for computing the gradient and Fisher information of Vecchia's Gaussian process loglikelihood approximation, which provides a computationally effi…
Smooth Density Spatial Quantile Regression
Halley Brantley, Montserrat Fuentes, Joseph Guinness +1
We derive the properties and demonstrate the desirability of a model-based method for estimating the spatially-varying effects of covariates on the quantile function. By modeling t…
Baseline Drift Estimation for Air Quality Data Using Quantile Trend Filtering
Halley L. Brantley, Joseph Guinness, Eric C. Chi
We address the problem of estimating smoothly varying baseline trends in time series data. This problem arises in a wide range of fields, including chemistry, macroeconomics, and m…
Estimating Atmospheric Motion Winds from Satellite Image Data using Space-time Drift Models
Indranil Sahoo, Joseph Guinness, Brian J. Reich
Geostationary satellites collect high-resolution weather data comprising a series of images which can be used to estimate wind speed and direction at different altitudes. The Deriv…