Model Selection in Beta Regression Analysis Using Several Information Criteria and Heuristic Optimization

Emre Dünder; Mehmet Ali Cengiz

EN

Model Selection in Beta Regression Analysis Using Several Information Criteria and Heuristic Optimization

Abstract

In the context of generalized linear modelling (GLM), the beta regression analysis is used to estimate regression models when the dependent variable lies between (0,1). In this paper, we carried out a model selection process using several information criteria with heuristic optimization. We employed the differential evolution algorithm as a heuristic optimization method to select the best model for beta regression analysis. The results show that the alternative-type information criteria provide competitive results during the model selection process in beta regression analysis.

Keywords

Beta regression, differential evolution algorithm, information criteria, model selection

References

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Details

Primary Language

English

Subjects

Applied Mathematics

Journal Section

Research Article

Authors

Emre Dünder ^*
0000-0003-0230-8968
Türkiye

Mehmet Ali Cengiz
0000-0002-1271-2588
Türkiye

Publication Date

December 31, 2020

Submission Date

December 7, 2020

Acceptance Date

December 17, 2020

Published in Issue

Year 2020 Number: 33

IZ

https://izlik.org/JA76RJ62HC

APA

Dünder, E., & Cengiz, M. A. (2020). Model Selection in Beta Regression Analysis Using Several Information Criteria and Heuristic Optimization. Journal of New Theory, 33, 76-84. https://izlik.org/JA76RJ62HC

AMA

1.Dünder E, Cengiz MA. Model Selection in Beta Regression Analysis Using Several Information Criteria and Heuristic Optimization. JNT. 2020;(33):76-84. https://izlik.org/JA76RJ62HC

Chicago

Dünder, Emre, and Mehmet Ali Cengiz. 2020. “Model Selection in Beta Regression Analysis Using Several Information Criteria and Heuristic Optimization”. Journal of New Theory, nos. 33: 76-84. https://izlik.org/JA76RJ62HC.

EndNote

Dünder E, Cengiz MA (December 1, 2020) Model Selection in Beta Regression Analysis Using Several Information Criteria and Heuristic Optimization. Journal of New Theory 33 76–84.

IEEE

[1]E. Dünder and M. A. Cengiz, “Model Selection in Beta Regression Analysis Using Several Information Criteria and Heuristic Optimization”, JNT, no. 33, pp. 76–84, Dec. 2020, [Online]. Available: https://izlik.org/JA76RJ62HC

ISNAD

Dünder, Emre - Cengiz, Mehmet Ali. “Model Selection in Beta Regression Analysis Using Several Information Criteria and Heuristic Optimization”. Journal of New Theory. 33 (December 1, 2020): 76-84. https://izlik.org/JA76RJ62HC.

JAMA

1.Dünder E, Cengiz MA. Model Selection in Beta Regression Analysis Using Several Information Criteria and Heuristic Optimization. JNT. 2020;:76–84.

MLA

Dünder, Emre, and Mehmet Ali Cengiz. “Model Selection in Beta Regression Analysis Using Several Information Criteria and Heuristic Optimization”. Journal of New Theory, no. 33, Dec. 2020, pp. 76-84, https://izlik.org/JA76RJ62HC.

Vancouver

1.Emre Dünder, Mehmet Ali Cengiz. Model Selection in Beta Regression Analysis Using Several Information Criteria and Heuristic Optimization. JNT [Internet]. 2020 Dec. 1;(33):76-84. Available from: https://izlik.org/JA76RJ62HC