Comparing regression methods with non-Gaussian stable errors

Author(s):

Reza Alizadeh Noughabi , Adel Mohammadpour *

Message:
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Nolan and Ojeda-Revah (2013) 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 significant of regression coefficients is proposed. Also, confidence intervals based on Fisher information for Nolan and Ojeda-Revah (2013) method, called NOR, and LRT are computed and compared with well-known methods. At the end we provide some guidance for various error distributions in heavy-tailed cases.
Keywords:

Regression , Quantile regression , Stable distribution , Ordinary least squares , Maximum likelihood

Language:
English
Published:
AUT Journal of Mathematics and Computing, Volume:3 Issue: 1, Feb 2022
Pages:
77 to 91
https://www.magiran.com/p2450759