Abstract
Interpolation methods fit a model to a given objective function by evaluating the objective function at, say, M points of a grid. If the model has, say, N independent coefficients which have to be determined, they are found by solving a set of M linear simultaneous equations in N unknowns. In this paper the effect on these methods is tested of enlarging the size of the grid ( M) to include more than N points. Numerical results show that the optimal data grid size tends to occur when M = N.
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