Abstract
In some regression model, the minimum (asymptotic) variance estimator of a ratio is discussed for some class of linear combinations of ratio estimators, and the jackknife procedure is considered. It is seen that the grouped jackknife estimator is optimal in the sense that it has asymptotically the minimum variance in the class. Higher order bias reduction of the estimators is discussed, and some examples are given.
