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A new robust regression method based on particle swarm optimization

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A new robust regression method based on particle swarm optimization. / Cagcag, Ozge; Yolcu, Ufuk; Egrioglu, Erol.
In: Communications in Statistics - Theory and Methods, Vol. 44, No. 6, 19.03.2015, p. 1270-1280.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Cagcag, O, Yolcu, U & Egrioglu, E 2015, 'A new robust regression method based on particle swarm optimization', Communications in Statistics - Theory and Methods, vol. 44, no. 6, pp. 1270-1280. https://doi.org/10.1080/03610926.2012.718843

APA

Cagcag, O., Yolcu, U., & Egrioglu, E. (2015). A new robust regression method based on particle swarm optimization. Communications in Statistics - Theory and Methods, 44(6), 1270-1280. https://doi.org/10.1080/03610926.2012.718843

Vancouver

Cagcag O, Yolcu U, Egrioglu E. A new robust regression method based on particle swarm optimization. Communications in Statistics - Theory and Methods. 2015 Mar 19;44(6):1270-1280. doi: 10.1080/03610926.2012.718843

Author

Cagcag, Ozge ; Yolcu, Ufuk ; Egrioglu, Erol. / A new robust regression method based on particle swarm optimization. In: Communications in Statistics - Theory and Methods. 2015 ; Vol. 44, No. 6. pp. 1270-1280.

Bibtex

@article{60123b8af2704ecd8fc15e18f091ae85,
title = "A new robust regression method based on particle swarm optimization",
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.",
keywords = "Linear model, Particle swarm optimization, Robust regression estimator, Simulation",
author = "Ozge Cagcag and Ufuk Yolcu and Erol Egrioglu",
year = "2015",
month = mar,
day = "19",
doi = "10.1080/03610926.2012.718843",
language = "English",
volume = "44",
pages = "1270--1280",
journal = "Communications in Statistics - Theory and Methods",
issn = "0361-0926",
publisher = "Taylor and Francis Ltd.",
number = "6",

}

RIS

TY - JOUR

T1 - A new robust regression method based on particle swarm optimization

AU - Cagcag, Ozge

AU - Yolcu, Ufuk

AU - Egrioglu, Erol

PY - 2015/3/19

Y1 - 2015/3/19

N2 - 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.

AB - 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.

KW - Linear model

KW - Particle swarm optimization

KW - Robust regression estimator

KW - Simulation

U2 - 10.1080/03610926.2012.718843

DO - 10.1080/03610926.2012.718843

M3 - Journal article

AN - SCOPUS:84961368828

VL - 44

SP - 1270

EP - 1280

JO - Communications in Statistics - Theory and Methods

JF - Communications in Statistics - Theory and Methods

SN - 0361-0926

IS - 6

ER -