new location prediction by Gaussian process method, and the marginal mean and variance of the new location is estimated by neighboring information; it gives 0.025-, 0.975- and 0.5-th conditional quantiles of the conditional distribution for each new location, at time n, conditional on observed locations at time n-1 and n; both point and interval predictions are provided
Predictions.GP(par,Y,s.ob,s.new,isotropic)parameters in the copula function
observed data
coordinates of observed locations
coordinates of new locations
indicator, True for isotropic correlation matrix, False for anisotropic correlation matrix, and we usually choose False for flexibility
0.025-, 0.975- and 0.5-th conditional quantiles of the conditional distribution for each new location, at time n
Yanlin Tang, Huixia Judy Wang, Ying Sun, Amanda Hering. Copula-based semiparametric models for spatio-temporal data.