Prediction of spatial functional random processes: Comparing functional and spatio-temporal kriging approaches

TL;DR

This paper compares functional and spatio-temporal kriging methods for predicting spatial functional random processes, evaluating their performance and computational efficiency through simulations and real data analysis.

Contribution

It provides a comparative analysis of OKFD and Sp.T. kriging, including new theoretical results and practical insights into their performance and computational costs.

Findings

OKFD and PWFK coincide under certain conditions.

Functional kriging performs better for small samples and non-stationary processes.

OKFD has significantly lower computational time.

Abstract

In this paper, we present and compare functional and spatio-temporal (Sp.T.) kriging approaches to predict spatial functional random processes (which can also be viewed as Sp.T. random processes). Comparisons with respect to computational time and prediction performance via functional cross-validation is evaluated, mainly through a simulation study but also on two real data sets. 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 functional kriging total model, coincide with OKFD in several situations. We contribute with new knowledge by proving that OKFD and PWFK coincide under certain conditions. From the simulation study, it is concluded that the prediction performance for the two kriging approaches in general is rather equal for stationary Sp.T. processes, with a tendency for functional kriging to work better for small sample sizes and Sp.T. kriging to work better for large sample 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 sample size. For all simulated cases, the computational time for OKFD was considerably lower compared to those for the Sp.T. kriging methods.