Nonparametric Modal Regression

@inproceedings{Chen2014NonparametricMR,
  title={Nonparametric Modal Regression},
  author={Yen-Chi Chen and Christopher R. Genovese and Ryan J. Tibshirani and Larry A. Wasserman},
  year={2014}
}
Modal regression estimates the local modes of the distribution of Y given X = x, instead of the mean, as in the usual regression sense, and can hence reveal important structure missed by usual regression methods. We study a simple nonparametric method for modal regression, based on a kernel density estimate (KDE) of the joint distribution of Y and X. We derive asymptotic error bounds for this method, and propose techniques for constructing confidence sets and prediction sets. The latter is used… CONTINUE READING

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