A Characterization Theorem for the Discrete Best Monotonic Approximation Problem
نویسنده
چکیده
A characterization theorem is derived that motivates a procedure for generating discrete best monotonie approximations to n sequential data values, when a strictly convex objective function is used in the calculation. The procedure is highly useful in the discrete nonlinear optimization calculation that produces the best piecewise monotonie approximations to the data.
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تاریخ انتشار 2010