Calculate correlation for separable model
.cor_sep(spatial, temporal, par_s, par_t)Correlations for separable model.
Pure spatial model, exp or cauchy for now.
Pure temporal model, exp or cauchy for now.
Parameters for the pure spatial model. Nugget effect supported.
Parameters for the pure temporal model.
The separable model is the product of a pure temporal model, \(C_T(u)\), and a pure spatial model, \(C_S(\mathbf{h})\). It is of the form $$C(\mathbf{h}, u)=C_{T}(u) \left[(1-\text{nugget})C_{S}(\mathbf{h})+\text{nugget} \delta_{\mathbf{h}=0}\right],$$ where \(\delta_{x=0}\) is 1 when \(x=0\) and 0 otherwise. Here \(\mathbf{h}\in\mathbb{R}^2\) and \(u\in\mathbb{R}\). Now only exponential and Cauchy correlation models are available.
Gneiting, T. (2002). Nonseparable, Stationary Covariance Functions for Space–Time Data, Journal of the American Statistical Association, 97:458, 590-600.