A Fast Algorithm for the Coordinate-wise Minimum Distance Estimation

Application of the minimum distance method to the linear regression model for estimating regression parameters is a difficult and time-consuming process due to the complexity of its distance function, and hence, it is computationally expensive. To deal with the computational cost, this paper proposes a fast algorithm which mainly uses technique of coordinate-wise minimization in order to estimate the regression parameters. R package based on the proposed algorithm and written in Rcpp is available online.