Confidence in Estimated Airframe Costs

Uncertainty Assessment in Aggregate Predictions

by Fred Timson, Dennis P. Tihansky


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Develops and applies a method for quantitative analysis of the uncertainty inherent in certain predictive models involving a number of regression equations, specifically the RAND airframe cost estimating model described in RAND/R-761/1-PR. The significant difference between this approach and R-761-PR/1 is that this presents uncertainty measures for models that exclude the production rate variable, while R-761/1-PR includes it. Only the logarithmic and exponential model forms were considered suitable for application to the RAND cost model. The analysis of the results indicated that, while costs predicted by both forms were not greatly different, the distributions of errors were very different. Also, the uncertainty bands for both were very wide, which suggests that acquisition program managers should not become committed too early to a given design approach or cost estimate.

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