Distribution Free Prediction Sets.

  title={Distribution Free Prediction Sets.},
  author={Jing Lei and James M. Robins and Larry A. Wasserman},
  journal={Journal of the American Statistical Association},
  volume={108 501},
This paper introduces a new approach to prediction by bringing together two different nonparametric ideas: distribution free inference and nonparametric smoothing. Specifically, we consider the problem of constructing nonparametric tolerance/prediction sets. We start from the general conformal prediction approach and we use a kernel density estimator as a measure of agreement between a sample point and the underlying distribution. The resulting prediction set is shown to be closely related to… CONTINUE READING
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