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Daouia, A., Girard, S. and Stupfler, G. (2019) Extreme M-Quantiles as Risk Measures: From L¹ to L^p Optimization. Bernoulli, 25, 264-309.
https://doi.org/10.3150/17-bej987

has been cited by the following article:

• TITLE: Introduction and Some Recent Advances in Lp Quantile Regression

  AUTHORS: Ying Sun, Fuming Lin

  KEYWORDS: Quantile, Expectile, Lp Quantile, Risk Measure

  JOURNAL NAME: Journal of Applied Mathematics and Physics, Vol.12 No.11, November 22, 2024

  ABSTRACT: As extremely important methods, Lp regression methods have attracted the attention of either theoretical or empirical researchers all over the world. As special cases of that, quantile and expectile regression (with p = 1 and p = 2, respectively) are well acquainted with. In contrast with them, general Lp regression (with p equals 1 and 2) has recently been found to have many unexpected properties by some studies, especially when 1 p Lp quantile regression under various p settings and shows some recent advances in Lp quantile regression, theoretically and empirically.