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Conditional Ordering Using Nonparametric Expectiles

Record type: Monograph (Working Paper)

Expectile regression, and more generally $M$-quantile regression, can be used to characterise the relationship between a response variable and explanatory variables when the behaviour of "non-average" individuals is of interest. The aim of this paper is to demonstrate how an individual's expectile-order, based on nonparametric estimation of the expectile regression function, can also be used to define a conditional ordering of the individual's value relative to the values of other members of a data set. The relationship between contextual, or "grouping", variables and this ordering can then be investigated. In particular, we propose five estimators of expectile-order, which we compare via simulation. The use of estimated expectile-order to investigate grouping effects is then illustrated using data on physician prescribing behaviour in the Midi-Pyrenees region of France during 1999.

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Citation

Aragon, Yves, Casanova, Sandrine, Chambers, Ray and Leconte, Eve (2005) Conditional Ordering Using Nonparametric Expectiles , Southampton, UK Southampton Statistical Sciences Research Institute 23pp. (S3RI Methodology Working Papers, M05/01).

More information

Published date: 25 January 2005

Identifiers

Local EPrints ID: 14071
URI: http://eprints.soton.ac.uk/id/eprint/14071
PURE UUID: b9a05ae0-33d7-4221-9da7-3bc8b495eb2b

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Date deposited: 26 Jan 2005
Last modified: 17 Jul 2017 16:59

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Contributors

Author: Yves Aragon
Author: Sandrine Casanova
Author: Ray Chambers
Author: Eve Leconte

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