APPROACHES TO MODEL TRANSFERABILITY AND UPDATING: THE COMBINED TRANSFER ESTIMATOR

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.

Media Info

  • Media Type: Print
  • Features: Figures; References;
  • Pagination: pp 1-7
  • Monograph Title: Urban travel forecasting
  • Serial:

Subject/Index Terms

Filing Info

  • Accession Number: 00476105
  • Record Type: Publication
  • ISBN: 0309046505
  • Files: TRIS, TRB, ATRI
  • Created Date: Sep 30 1988 12:00AM