The Gaussian correlation structure uses the product exponential correlation function with a power of 2 as the estimated model. This model assumes that Y is normally distributed with mean μ and covariance matrix σ2R. The elements of the R matrix are defined as follows:

The Cubic correlation structure also assumes that Y is normally distributed with mean μ and covariance matrix σ2R. The R matrix consists of the following elements:

For more information, see Santer (2003). The theta parameter used in the Cubic correlation structure is the reciprocal of the parameter often used in the literature. The reciprocal is used so that when theta has no effect on the model, then rho has a value of zero, rather than infinity.