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Journal of the American Statistical Association Volume 114, 2019 - Issue 527
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Theory and Methods

Extremiles: A New Perspective on Asymmetric Least Squares

Abdelaati DaouiaToulouse School of Economics, University of Toulouse Capitole, Toulouse, FranceORCID Iconhttps://orcid.org/0000-0003-2621-8860View further author information
ORCID Icon,
Irène GijbelsDepartment of Mathematics and Leuven Statistics Research Centre, Katholieke Universiteit Leuven, Leuven, BelgiumCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0002-4443-9803View further author information
ORCID Icon &
Gilles StupflerSchool of Mathematical Sciences, University of Nottingham, Nottingham, United KingdomORCID Iconhttps://orcid.org/0000-0003-2497-9412View further author information
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Pages 1366-1381 | Received 01 Jun 2017, Published online: 29 Oct 2018

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Taoufik Bouezmarni, Mohamed Doukali & Abderrahim Taamouti. (2024) Testing Granger non-causality in expectiles. Econometric Reviews 43:1, pages 30-51.
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Lukas Arnroth & Johan Vegelius. (2023) Quantile regression based on the skewed exponential power distribution. Communications in Statistics - Simulation and Computation 0:0, pages 1-17.
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Abdelaati Daouia, Irène Gijbels & Gilles Stupfler. (2022) Extremile Regression. Journal of the American Statistical Association 117:539, pages 1579-1586.
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Ibrahim M. Almanjahie, Salim Bouzebda, Zoulikha Kaid & Ali Laksaci. (2022) Nonparametric estimation of expectile regression in functional dependent data. Journal of Nonparametric Statistics 34:1, pages 250-281.
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Articles from other publishers (13)

Rong Jiang & Keming Yu. (2024) Rong Jiang and Keming Yu's contribution to the Discussion of ‘Estimating means of bounded random variables by betting’ by Waudby-Smith and Ramdas. Journal of the Royal Statistical Society Series B: Statistical Methodology 86:1, pages 38-39.
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Michaël Allouche, Jonathan El Methni & Stéphane Girard. (2022) A refined Weissman estimator for extreme quantiles. Extremes 26:3, pages 545-572.
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Yu Chen, Mengyuan Ma & Hongfang Sun. (2023) Statistical inference for extreme extremile in heavy-tailed heteroscedastic regression model. Insurance: Mathematics and Economics 111, pages 142-162.
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Christian Genest & Matthias Scherer. (2023) When copulas and smoothing met: An interview with Irène Gijbels. Dependence Modeling 11:1.
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Hristos Tyralis, Georgia Papacharalampous & Sina Khatami. (2023) Expectile-based hydrological modelling for uncertainty estimation: Life after mean. Journal of Hydrology 617, pages 128986.
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Yimin Xiong, Zhi Zheng & Weiping Zhang. (2023) Variable selection in high-dimensional extremile regression via the quasi elastic net. JUSTC 53:2, pages 1.
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Juxia Xiao, Ping Yu, Xinyuan Song & Zhongzhan Zhang. (2022) Statistical inference in the partial functional linear expectile regression model. Science China Mathematics 65:12, pages 2601-2630.
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Laurent Gardes. (2022) On tail-risk measures for non-integrable heavy-tailed random variables. Econometrics and Statistics.
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Stéphane Girard, Gilles Stupfler & Antoine Usseglio-Carleve. (2021) Extreme conditional expectile estimation in heavy-tailed heteroscedastic regression models. The Annals of Statistics 49:6.
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Joonpyo Kim, Seoncheol Park, Junhyeon Kwon, Yaeji Lim & Hee-Seok Oh. (2021) Estimation of spatio-temporal extreme distribution using a quantile factor model. Extremes 24:1, pages 177-195.
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Mustapha Mohammedi, Salim Bouzebda & Ali Laksaci. (2021) The consistency and asymptotic normality of the kernel type expectile regression estimator for functional data. Journal of Multivariate Analysis 181, pages 104673.
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Abdelaati Daouia, Stéphane Girard & Gilles Stupfler. (2020) Tail expectile process and risk assessment. Bernoulli 26:1.
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Gilles Stupfler. (2019) On a relationship between randomly and non-randomly thresholded empirical average excesses for heavy tails. Extremes 22:4, pages 749-769.
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