Corpus ID: 235899184

Nonparametric, tuning-free estimation of S-shaped functions

@inproceedings{Feng2021NonparametricTE,
  title={Nonparametric, tuning-free estimation of S-shaped functions},
  author={Oliver Y. Feng and Yining Chen and Qiyang Han and Raymond J. Carroll and Richard J. Samworth},
  year={2021}
}
We consider the nonparametric estimation of an S-shaped regression function. The least squares estimator provides a very natural, tuning-free approach, but results in a non-convex optimisation problem, since the inflection point is unknown. We show that the estimator may nevertheless be regarded as a projection onto a finite union of convex cones, which allows us to propose a mixed primal-dual bases algorithm for its efficient, sequential computation. After developing a projection framework… Expand