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Quantile regression

Nature Methods volume 16, pages 451–452 (2019)Cite this article

Quantile regression robustly estimates the typical and extreme values of a response.

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Fig. 1: Distributions, quantile profiles and quantile regression (QR) of birth weight, W, as a function of gestational age, A.
Fig. 2: Precision and accuracy in quantile regression (QR).
Fig. 3: Regression diagnostics that suggest quantile regression (QR) should be used.

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Authors and Affiliations

  1. Faculty member, Indian Statistical Institute, Kolkata, India

    Kiranmoy Das

  2. Staff scientist, Canada’s Michael Smith Genome Sciences Centre, Vancouver, BC, Canada

    Martin Krzywinski

  3. Professor of Statistics, The Pennsylvania State University, University Park, PA, USA

    Naomi Altman

Authors
  1. Kiranmoy Das
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  2. Martin Krzywinski
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  3. Naomi Altman
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Corresponding author

Correspondence to Martin Krzywinski.

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The authors declare no competing interests.

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Das, K., Krzywinski, M. & Altman, N. Quantile regression. Nat Methods 16, 451–452 (2019). https://doi.org/10.1038/s41592-019-0406-y

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