Comparing Regression Methods With Non-Gaussian Stable Errors

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 significant of regression coefficients is proposed. also, confidence intervals based on fisher information 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 distributions in heavy-tailed caese.