Optimal Algorithms for Unimodal Regression

@inproceedings{Stout2000OptimalAF,
  title={Optimal Algorithms for Unimodal Regression},
  author={Quentin F. Stout},
  year={2000}
}
This paper gives optimal algorithms for determining realvalued univariate unimodal regressions, that is, for determining the optimal regression which is increasing and then decreasing. Such regressions arise in a wide variety of applications. They are a form of shape-constrained nonparametric regression, closely related to isotonic regression. For the L2 metric our algorithm requires only (n) time for regression on n points, while for theL1 metric it requires (n logn) time. Previous algorithms… CONTINUE READING
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