An Alternative Procedure for Estimating Unit Learning Curves

Abstract

Abstract : The unit learning curve plays a prominent role in DOD cost analysis. In those cases where the model accurately describes the real-life situation, i.e., when the model is properly applied to the data, it can be a powerful tool for predicting unit production costs. There are, however, some unique estimation problems inherent in the model. The usual method of generating predicted unit production costs attempts to extend properties of least squares estimators to non-linear functions of these estimators. The result is biased estimates of unit production costs. Another problem common to many learning curve applications is estimating lot midpoints and slope coefficients when both estimates depend on each other and both quantities are unknown. This paper addresses the two problems discussed above and presents an alternative procedure for estimating unit learning curves.