Outlier Identification Via Non-parametric Expectile-order
Aragon, Yves, Chambers, Ray, Leconte, Eve and Poiraud-Casanova, Sandrine (2003) Outlier Identification Via Non-parametric Expectile-order. Southampton, UK, Southampton Statistical Sciences Research Institute, 23pp. (S3RI Methodology Working Papers, M03/12).
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Non-parametric conditional expectiles can be used to characterise the relationship between a response variable and explanatory variables when the behaviour of “outlier” individuals is of interest. The aim of this paper is to demonstrate how an individual’s expectile-order, based on a non-parametric approximation to the expectile regression function, can be used as a measure of the extremity of that individual’s value relative to the values of other members of a dataset. In particular, we propose five estimators of this expectile-order which we compare via simulation. The use of expectile-order to characterise outliers or extreme values is then illustrated using a dataset of prescribing behaviour by physicians in the Midi-Pyrenees region of France during 1999. THIS DOCUMENT HAS BEEN SUPERSEDED BY M05/01.
|Item Type:||Monograph (UNSPECIFIED)|
|Subjects:||H Social Sciences > HA Statistics|
|Divisions:||University Structure - Pre August 2011 > Southampton Statistical Sciences Research Institute
|Date Deposited:||11 Jul 2004|
|Last Modified:||07 Oct 2015 13:11|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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