Parametric Nonstationary Covariance Functions On Spheres

Abstract

Gaussian Processes are powerful tools for modeling spatial data. In this context, a significant amount of modeling focus is placed on specifying the covariance function, required to be symmetric and positive definite. Covariance functions have classically been defined and used in Euclidean space. However, as data collected from the globe becomes more prevalent, accounting for Earth’s geometry becomes increasingly important. Using Euclidean distance can be suboptimal for these data. We survey the literature for recent developments related to construction of nonstationary covariance functions on spheres, which historically has been a challenging area. We present contributions in this effort by providing three general forms for families of parametric nonstationary covariance functions.