meig: Moran eigenvectors and eigenvalues. Output from meigen or meigen_f
coords0: Matrix of spatial point coordinates of prediction sites (N_0 x 2)
coords_z0: Optional. One- or two-column matrix whose t-th column represents the t-th temporal coordinate of prediction times (N_0 x 1 or N_0 x 2).
s_id0: Optional. ID specifying groups modeling spatial effects (N_0 x 1). If specified, Moran eigenvectors are extracted by groups. It is useful e.g. for multilevel modeling (s_id is the groups) and panel data modeling (s_id is given by individual location id). Default is NULL
Returns
sf: Matrix of the first L eigenvectors at unobserved sites (N_0 x L)
ev: Vector of the first L eigenvalues (L x 1)
sf_z: List. t-th element is the matrix of the t-th temporal eigenvectors (N x L_t)
ev_z: List. t-th element is the vector of the t-th temporal eigenvalues (L_t x 1)
other: List of other outputs, which are internally used
References
Drineas, P. and Mahoney, M.W. (2005) On the Nystrom method for approximating a gram matrix for improved kernel-based learning. Journal of Machine Learning Research, 6 (2005), 2153-2175.