A question if I may.
In applications where prior statistical data is either sparse, incomplete or not directly comparable, using Bayesian techniques may offer advantages over traditional techniques. This is a problem in the aerospace industry, for example, where cost data from previous projects is limited and usually not directly comparable to the current application; using Bayesian priors may allow more effective and more rigorous use of this data. Is anyone aware of any work that has been done in using Bayesian ideas to compensate for incomplete and limited information?
Many thanks
Andrew Williamson
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Dr A Williamson
Imperial College London
Prince Consort Road
London SW7 2AZ
Tel: 0207 594 7631
Fax: 0207 594 7714
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