Robust parameter estimation of regression model with AR(p) error terms

ABSTRACT

In this article, we consider a linear regression model with AR(p) error terms with the assumption that the error terms have a t distribution as a heavy-tailed alternative to the normal distribution. We obtain the estimators for the model parameters by using the conditional maximum likelihood (CML) method. We conduct an iteratively reweighting algorithm (IRA) to find the estimates for the parameters of interest. We provide a simulation study and three real data examples to illustrate the performance of the proposed robust estimators based on t distribution.

KEYWORDS:

• Autoregressive stationary process
• Conditional maximum likelihood
• Linear regression
• Non-normal distributions
• Robust estimation

MATHEMATICAL SUBJECT CLASSIFICATION:

• 62F10
• 62f35
• 68U20

Acknowledgments

The authors thank the anonymous referee, the editor and the associate editor whose comments, suggestions, and corrections have led to a considerable improvement of this article.