Publication:
Learning Curve and Rate Adjustment Models: An Investigation of Bias

Loading...
Thumbnail Image
Authors
Moses, O. Douglas
Subjects
Cost estimation, cost analysis, learning curve, production rate, prediciton, forecasting
Advisors
Date of Issue
1991-02
Date
1991-02
Publisher
Monterey, California. Naval Postgraduate School
Language
Abstract
Learning curve models have gained widespread acceptance as a technique for analyzing and forecasting the cost of item produced from a repetitive process. Considerable research has investigated augmenting the traditional learning curve model with the addition of a production rate variable, creating a rate adjustment model. This study compares the forecasting bias of the learning curve and rate adjustment models. A simulation methodology is used to vary conditions along seven dimensions. The magnitude and direction of errors in future cost estimates are analyzed and compared under the various simulated conditions, using ANOVA. Overall results indicate that the rate adjustment model is generally unbiased. If the cost item being forecast contains any element that is not subject to learning them the traditional learning curve model is consistently biased toward underestimation of future cost. Conditions when the bias is strongest are identified.
Type
Technical Report
Description
Series/Report No
Department
Administrative Sciences
Identifiers
NPS Report Number
NPS-AS-91-005
Sponsors
Funder
O&MN, Direct Funding
Format
Citation
Distribution Statement
Approved for public release; distribution is unlimited.
Rights
Collections