Adaptive warped kernel estimators

@inproceedings{Chagny2017AdaptiveWK,
  title={Adaptive warped kernel estimators},
  author={Ga{\"e}lle Chagny},
  year={2017}
}
In this work, we develop a method of adaptive nonparametric estimation, based on "warped" kernels. The aim is to estimate a real-valued function s from a sample of random couples (X,Y ). We deal with transformed data (Φ(X), Y ), with Φ a one-to-one function, to build a collection of kernel estimators. The data-driven bandwidth selection is done with a method inspired by Goldenshluger and Lepski (2011). The method permits to handle various problems such as additive and multiplicative regression… CONTINUE READING