Comparing regression methods with non-Gaussian stable errors

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

Alizadeh Noughabi Reza; MOHAMMADPOUR ADEL

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: AUT Journal of Mathematics and Computing Year:2022 | Volume:3 | Issue:1 Page(s): 77-91

Download Full-Text

View:

Download:

Cites:

Information Journal Paper

Title

Comparing regression methods with non-Gaussian stable errors

Author(s)

Alizadeh Noughabi Reza | MOHAMMADPOUR ADEL | Issue Writer Certificate

Keywords

Regression

Quantile regression

Stable distribution

Ordinary least squares

Maximum likelihood

Abstract

Nolan and Ojeda-Revah in [16] proposed a Regression model with heavy-tailed stable errors. In this paper, we extend this method for multivariate heavy-tailed errors. Furthermore, A likelihood ratio test (LRT) for testing signi, cant of Regression coe, cients is proposed. Also, con, dence intervals based on , sher in-formation for [16] method, called NOR, and LRT are computed and compared with well-known methods. In the end, we provide some guidance for various error distri-butions in heavy-tailed cases.

Multimedia

No record.

Cites

No record.

References

No record.

Cite

APA: Copy

Alizadeh Noughabi, Reza, & MOHAMMADPOUR, ADEL. (2022). Comparing regression methods with non-Gaussian stable errors. AUT JOURNAL OF MATHEMATICS AND COMPUTING, 3(1), 77-91. SID. https://sid.ir/paper/1043894/en

Vancouver: Copy

Alizadeh Noughabi Reza, MOHAMMADPOUR ADEL. Comparing regression methods with non-Gaussian stable errors. AUT JOURNAL OF MATHEMATICS AND COMPUTING[Internet]. 2022;3(1):77-91. Available from: https://sid.ir/paper/1043894/en

IEEE: Copy

Reza Alizadeh Noughabi, and ADEL MOHAMMADPOUR, “Comparing regression methods with non-Gaussian stable errors,” AUT JOURNAL OF MATHEMATICS AND COMPUTING, vol. 3, no. 1, pp. 77–91, 2022, [Online]. Available: https://sid.ir/paper/1043894/en

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans

No record.

Recommended Workshops