A0236
Title: Prediction of spatial functional random processes: Comparing functional and spatio-temporal kriging approaches
Authors: Sara Sjostedt-de Luna - Umea University (Sweden) [presenting]
Johan Strandberg - Umea University (Sweden)
Jorge Mateu - University Jaume I (Spain)
Abstract: Functional and spatio-temporal (Sp.T.) kriging approaches to predict spatial functional random processes (which can also be viewed as Sp.T. random processes) are compared. Comparisons with respect to computational time and prediction performance via functional cross-validation are evaluated, mainly through a simulation study, but also on a real data set. We restrict comparisons to Sp.T. kriging versus ordinary kriging for functional data (OKFD), since the more flexible functional kriging approaches pointwise functional kriging (PWFK) and the functional kriging total model coincide with OKFD in several situations. We formulate conditions under which we show that OKFD and PWFK coincide. From the simulation study, it is concluded that the prediction performance of the two kriging approaches in general is rather equal for stationary Sp.T. processes. However, functional kriging tends to perform better for small sample sizes, while Sp.T. works better for large sizes. For non-stationary Sp.T. processes, with a common deterministic time trend and/or time varying variances and dependence structure, OKFD performs better than Sp.T. kriging irrespective of the sample size. For all simulated cases, the computational time for OKFD was considerably lower compared to those for the Sp.T. kriging methods.
