Huber-Dutter estimation of linear models with dependent errors

Abstract

In this article, we investigate a linear model that incorporates stationary causal processes, with a focus on utilizing Huber-Dutter methods to investigate the estimators of unknown parameters and a scale for the errors. Our results indicate that the Huber-Dutter methods can effectively be utilized for linear models that feature errors, which are short-range dependent linear processes, heavy-tailed linear processes, as well as some commonly used non linear time series.