On elliptical quantiles in the quantile regression setup
This article defines a meaningful concept of elliptical location quantile with the aid of quantile regression, discusses its basic properties, and suggests its extension to a general regression framework through a locally constant nonparametric approach.
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Volume (Year): 116 (2013)
Issue (Month): C ()
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References listed on IDEAS
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- Paindaveine, Davy & Siman, Miroslav, 2011.
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- Marc Hallin & Davy Paindaveine & Miroslav Siman, 2008.
"Multivariate quantiles and multiple-output regression quantiles: from L1 optimization to halfspace depth,"
Working Papers ECARES
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- Marc Hallin & Davy Paindaveine & Miroslav Šiman, 2010. "Multivariate quantiles and multiple-output regression quantiles: From L1 optimization to halfspace depth," ULB Institutional Repository 2013/127979, ULB -- Universite Libre de Bruxelles.
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- Ella Roelant & Stefan Aelst & Gert Willems, 2009. "The minimum weighted covariance determinant estimator," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 70(2), pages 177-204, September.
- Koenker,Roger, 2005.
Cambridge University Press, number 9780521845731, December.
- Ella Roelant & Stefan Aelst, 2007. "An L1-type estimator of multivariate location and shape," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 15(3), pages 381-393, February.
- Polonik, Wolfgang, 1997. "Minimum volume sets and generalized quantile processes," Stochastic Processes and their Applications, Elsevier, vol. 69(1), pages 1-24, July.
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