Universiti Teknologi Malaysia Institutional Repository

Identifying multiple outliers in linear regression : robust fit and clustering approach

Adnan, Robiah and Setan, Halim and Mohammad, M N (2001) Identifying multiple outliers in linear regression : robust fit and clustering approach. In: The 10th FIG International Symposium on Deformation Measurements, 19 – 22 March 2001, Orange,,California,USA.

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Abstract

This research provides a clustering based approach for determining potential candidates for outliers.This is a modification of the method proposed by Serbert et.al (1998).It is based on using the single linkage clustering algorithm to group the standardized predicted and residual values of data set fit by least trimmed of squares (LTS).

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:least trimmed of squares, regression, clustering algorithm
Subjects:T Technology > TA Engineering (General). Civil engineering (General)
Divisions:Geoinformation Science And Engineering (Formerly known)
ID Code:1215
Deposited By: En. Tajul Ariffin Musa
Deposited On:01 Mar 2007 02:56
Last Modified:01 Jun 2010 02:52

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