STATISTICAL INTERPRETATION OF PREDICTIONS WITH DISAGGREGATE DEMAND MODELS.

This paper discusses an element of forecasting with disaggregate demand models, the extent to which the accuracy of the final prediction depends on the accuracy of the calibration process. The paper introduces a numerical technique to evaluate approximate confidence intervals for the expected number of people using a transportation facility and approximate prediction intervals for the actual usage. The degree of accuracy that can be obtained with different parameter variances is illustrated numerically for the binary probit model.