A new robust regression method based on particle swarm optimization

Cagcag, Ozge and Yolcu, Ufuk and Egrioglu, Erol (2015) A new robust regression method based on particle swarm optimization. Communications in Statistics - Theory and Methods, 44 (6). pp. 1270-1280. ISSN 0361-0926

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Abstract

Regression analysis is one of methods widely used in prediction problems. Although there are many methods used for parameter estimation in regression analysis, ordinary least squares (OLS) technique is the most commonly used one among them. However, this technique is highly sensitive to outlier observation. Therefore, in literature, robust techniques are suggested when data set includes outlier observation. Besides, in prediction a problem, using the techniques that reduce the effectiveness of outlier and using the median as a target function rather than an error mean will be more successful in modeling these kinds of data. In this study, a new parameter estimation method using the median of absolute rate obtained by division of the difference between observation values and predicted values by the observation value and based on particle swarm optimization was proposed. The performance of the proposed method was evaluated with a simulation study by comparing it with OLS and some other robust methods in the literature.

Item Type: Journal Article
Journal or Publication Title: Communications in Statistics - Theory and Methods
Uncontrolled Keywords: /dk/atira/pure/subjectarea/asjc/2600/2613
Subjects:
Departments: Lancaster University Management School > Management Science
ID Code: 139465
Deposited By: ep_importer_pure
Deposited On: 09 Dec 2019 11:55
Refereed?: Yes
Published?: Published
Last Modified: 11 Feb 2020 05:44
URI: https://eprints.lancs.ac.uk/id/eprint/139465

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