Quantile Regression

Koenker, R. (2005). Quantile Regression. Cambridge University Press.

Type

Book

Intellectual base

Review or monograph

Year

2005

DOI

10.1017/cbo9780511754098

ISBN

9780511754098

DOI registrant

Cambridge University Press

Link

https://doi.org/10.1017/cbo9780511754098

Cited from

statistics_experimental_design

Cited by

2 citations across 2 artifacts.

Each citation links to the sentence it supports in the citing article.

Primes

• Nonparametric Methods
  • In econometrics, quantile regression (Koenker-Bassett 1978) estimates entire conditional distributions rather than conditional means, with applications in wage-distribution analysis, risk modeling, and robust prediction

    This sourceKoenker quantile regression robust conditional-distribution estimation.

    Supported in partVerified against the publisher's abstract

    Koenker's 2005 book abstract backs the frame — quantile regression models the whole response distribution, not just the conditional mean — but names economics, biology, ecology and finance as its applications, not the three listed.

    “By complementing the exclusive focus of classical least squares regression on the conditional mean, quantile regression offers a systematic strategy for examining how covariates influence the location, scale and shape of the entire response distribution.”

    Read by an automated reader; not a human review. How support was checked

Domain-specific

• Least absolute deviations
  • For example, the distinction between constitutive identity and a convenient observable transfers from For an intercept-only model, any sample median minimizes the sum of absolute deviations. to Linear LAD regression can be written as a linear program using nonnegative positive and negative residual variables..

Verification

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