Half-spectral space–time covariance models

We develop a new class of space–time Gaussian process models by specifying covariance functions using what we call a half-spectral representation. We establish general properties of half-spectral models and appeal to results on a screening effect analysis to claim more natural space–time interaction properties in the class of models we develop. To test this claim and to more generally test this class of models, we fit models we develop in this paper to a wind power dataset. We show our models fit these data better than other common separable and non-separable space–time models.