Spline smoothing under constraints on derivatives

An efficient algorithm for computing a smoothing polynomial splines under inequality constraints on derivatives is introduced where both order and breakpoints ofs can be prescribed arbitrarily. By using the B-spline representation ofs, the original semi-infinite constraints are replaced by stronger finite ones, leading to a least squares problem with linear inequality constraints. Then these constraints are transformed into simple box constraints by an appropriate substitution of variables so that efficient standard techniques for solving such problems can be applied. Moreover, the smoothing term commonly used is replaced by a cheaply computable approximation. All matrix transformations are realized by numerically stable Givens rotations, and the band structure of the problem is exploited as far as possible.

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