A maximum likelihood solution is presented for analyzing data which arise from a linear model whose error term is assumed to have variance proportional to some unknown power of the response. An efficient iterative method for solving the likelihood equations is obtained which incoporates use of a transfomation to orthogonalize the two variance paramaters. Assessments of the method are made through simulations study and the results are compared with those of the ordinary least squares. Examples from the literature are included to illustrate the method and also to compare the results with a weighted least squares estimates.