Title: Generalized Minimum Distance Estimators in Linear Regression with Dependent Errors,
Abstract: This paper discusses minimum distance estimation method in the linear
regression model with dependent errors which are strongly mixing. The
regression parameters are estimated through the minimum distance estimation
method, and asymptotic distributional properties of the estimators are
discussed. A simulation study compares the performance of the minimum distance
estimator with other well celebrated estimator. This simulation study shows the
superiority of the minimum distance estimator over another estimator. KoulMde
(R package) which was used for the simulation study is available online. See
section 4 for the detail.