Singular Value Decomposition As An Equation Solver In Co-Kriging Matrices - Synopsis

One of the most significant elements in solving the co-kriging equations is the matrix solver. In this paper, the singular value decomposition (SVD) as an equation solver is proposed to solve the co-kriging matrices. Given that other equation solvers have various drawbacks, the SVD presents an alternative for solving the co-kriging matrices. The SVD is briefly discussed, and its performance is compared with the banded Gaussian elimination that is most frequently used in co-kriging matrices by means of case studies. In spite of the increase in the memory requirement, the SVD yields better results.