Covariance–Based Rational Approximations of Fractional SPDEs for Computationally Efficient Bayesian Inference
Covariance–Based Rational Approximations of Fractional SPDEs for Computationally Efficient Bayesian Inference
The stochastic partial differential equation (SPDE) approach is widely used for modeling large spatial datasets. It is based on representing a Gaussian random field $u$ on $\mathbb{R}^d$ as the solution of an elliptic SPDE $L^\beta u = \mathcal{W}$ where $L$ is a second-order differential operator, $2\beta$ (belongs to natural number …