An Indirect Nonparametric Regression Method for One-Dimensional Continuous Distributions Using Warping Functions

Authors: Zhicheng Chen

Distributions play a very important role in many applications. Inspired by the newly developed warping transformation of distributions, an indirect nonparametric distribution to distribution regression method is proposed in this article for distribution prediction. Additionally, a hybrid approach by fusing the predictions respectively obtained by the proposed method and the conventional method is further developed for reducing risk when the predictor is contaminated.

Comments: 4 Pages.

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Submission history

[v1] 2017-04-22 03:09:39
[v2] 2017-05-12 21:34:09
[v3] 2017-06-02 14:03:25

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