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A generalized quantile regression model

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  • Vahid Nassiri
  • Ignace Loris

Abstract

A new class of probability distributions, the so-called connected double truncated gamma distribution, is introduced. We show that using this class as the error distribution of a linear model leads to a generalized quantile regression model that combines desirable properties of both least-squares and quantile regression methods: robustness to outliers and differentiable loss function.

Suggested Citation

  • Vahid Nassiri & Ignace Loris, 2013. "A generalized quantile regression model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(5), pages 1090-1105.
    • Handle: RePEc:taf:japsta:v:40:y:2013:i:5:p:1090-1105
    DOI: 10.1080/02664763.2013.780158
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    Cited by:

    1. Francisco J. Rubio Alvarez, 2020. "Letter to the Editor: ‘On Quantile‐based Asymmetric Family of Distributions: Properties and Inference’," International Statistical Review, International Statistical Institute, vol. 88(3), pages 793-796, December.
    2. Worku B. Ewnetu & Irène Gijbels & Anneleen Verhasselt, 2023. "Flexible two-piece distributions for right censored survival data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 29(1), pages 34-65, January.
    3. Irène Gijbels & Rezaul Karim & Anneleen Verhasselt, 2020. "Response to the Letter to the Editor on ‘On Quantile‐based Asymmetric Family of Distributions: Properties and Inference’," International Statistical Review, International Statistical Institute, vol. 88(3), pages 797-801, December.

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