Efficient Mean Estimation in Log-Normal Linear Models with First-Order Correlated Errors

In this paper, we propose a log-normal linear model whose errors arefirst-order correlated, and suggest a two-stage method for the efficient estimation ofthe conditional mean of the response variable at the original scale. We obtain twoestimators which minimize the asymptotic mean squared error (MM) and the asymptotic bias (MB), respectively. Both the estimators are very easy to implement, andsimulation studies show that they are perform better.