APPROACHES TO MODEL TRANSFERABILITY AND UPDATING: THE COMBINED TRANSFER ESTIMATOR

Author(s)
BEN-AKIVA, M BOLDUC, D
Year
Abstract

The idea of model transferability is to use previously estimatedmodel 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 combinedestimator is shown to have superior accuracy in a mean square errorsense 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. This paper appeared in transportation research record no. 1139, Urban travel forecasting. For covering abstract see IRRD no 817822.

Request publication

3 + 17 =
Solve this simple math problem and enter the result. E.g. for 1+3, enter 4.

Publication

Library number
I 817823 IRRD 8901
Source

TRANSP RES REC WASHINGTON D.C. USA U0361-1981 V0 309 04650 5 SERIAL 1987 1139 PAG:1-7 T7

Our collection

This publication is one of our other publications, and part of our extensive collection of road safety literature, that also includes the SWOV publications.