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Multivariate L-Moments Based on Transports

  • Alexis DecurningeEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9389)

Abstract

Univariate L-moments are expressed as projections of the quantile function onto an orthogonal basis of univariate polynomials. We present multivariate versions of L-moments expressed as collections of orthogonal projections of a multivariate quantile function on a basis of multivariate polynomials. We propose to consider quantile functions defined as transports from the uniform distribution on \([0;1]^d\) onto the distribution of interest and present some properties of the subsequent L-moments. The properties of estimated L-moments are illustrated for heavy-tailed distributions.

Keywords

Orthogonal Basis Quantile Function Optimal Transport Conditional Quantile Multivariate Extension 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

This work was performed during the PhD of A. Decurninge supported by the DGA/MRIS and Thales.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Mathematical and Algorithmic Sciences Lab, France Research CenterHuawei Technologies Co. Ltd.Boulogne-BillancourtFrance

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