SPATIAL AUTOREGRESSIVE ERROR-COMPONENTS IN TRAVEL FLOW MODELS

In this study, we propose a generalization of the error components formulation to model the correlation among the errors of a regression based on travel flow data. The error term is broken down into a sum of one component related to the origin zones, one component related to the destination zones and a remainder. The inter-dependencies among the errors are assumed to result from applying a first-order spatial autoregressive generating process to each component. An efficient estimation approach based on maximum likelihood is suggested to address the practical implementation of such a model with a large sample size.