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We present an algorithm to compute best least-squares approximations ofdiscrete real-valued functions by first-degree splines (broken lines) with freeknots. We demonstrate that the algorithm delivers after a finite number ofsteps a (global) best approximation. The analysis is complemented by remarks onprogramming and by a number of numerical examples including applications frommedicine (MBC, MIC).

Computing best discrete least-squares approximations by first-degree splines with free knots