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) ).
Download
Full text not available from this repository.
Description/Abstract
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 THIS DOCUMENT HAS BEEN SUPERSEDED BY M05/01.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) |
|---|---|
| Related URLs: | |
| Subjects: | H Social Sciences > HA Statistics |
| Divisions: | University Structure - Pre August 2011 > Southampton Statistical Sciences Research Institute |
| Item ID: | 8162 |
| Date Deposited: | 11 Jul 2004 |
| Last Modified: | 02 Mar 2012 12:24 |
| Contributors: | Aragon, Yves (Author) Chambers, Ray (Author) Leconte, Eve (Author) Poiraud-Casanova, Sandrine (Author) |
| Date: | 2003 |
| Status: | Published |
| Publisher: | Southampton Statistical Sciences Research Institute |
| URI: | http://eprints.soton.ac.uk/id/eprint/8162 |
Actions (login required)
 |
View Item |
