189 citations · 522 across the 27 of their papers we have counts for
4 papers · 1 filter
A Test for Isotropy on a Sphere using Spherical Harmonic Functions
Indranil Sahoo, Joseph Guinness, Brian J. Reich
Analysis of geostatistical data is often based on the assumption that the spatial random field is isotropic. This assumption, if erroneous, can adversely affect model predictions a…
Spectral Density Estimation for Random Fields via Periodic Embeddings
Joseph Guinness
We introduce methods for estimating the spectral density of a random field on a -dimensional lattice from incomplete gridded data. Data are iteratively imputed onto an expanded…
A Case Study Competition Among Methods for Analyzing Large Spatial Data
Matthew J. Heaton, Abhirup Datta, Andrew Finley +10
The Gaussian process is an indispensable tool for spatial data analysts. The onset of the "big data" era, however, has lead to the traditional Gaussian process being computationall…
A general framework for Vecchia approximations of Gaussian processes
Matthias Katzfuss, Joseph Guinness
Gaussian processes (GPs) are commonly used as models for functions, time series, and spatial fields, but they are computationally infeasible for large datasets. Focusing on the typ…