Title: APPROACHES TO MODEL TRANSFERABILITY AND UPDATING: THE COMBINED TRANSFER ESTIMATOR
Abstract: The idea of model transferability is to use previously estimated model parameters from a different area for model estimation. The combined transfer estimator is based on the mean squares error criterion and extends the Bayesian procedure to explicitly account for the presence of a transfer bias. The suggested estimator is easy to apply because it is expressed as a linear combination of the direct estimation results and the previously estimated parameters. The combined estimator is shown to have superior accuracy in a mean square error sense to a direct (unbiased nontransfer) estimator whenever the transfer bias is relatively small. Numerical examples of the transfer region--where the combined estimator is superior to the direct estimator--are provided.
Publication Year: 1987
Publication Date: 1987-01-01
Language: en
Type: article
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Cited By Count: 34
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