Volume 4 Number 1 Back Cover

Sandy Balkin and J. Keith Ord with discussion by Johannes Ledolter; Fontaine, Qu, Zimmerman, and Spiegelman; and Andrew Harvey Assessing the Impact of Speed-Limit Increases on...

Contributors

David Banks, Editor-in-Chief Susan Lapham, Associate Editor John V. Wells, Associate Editor Deborah Moore, Managing Editor Martha Courtney, Editor Marsha Fenn, Project Manager Lorisa Smith, Editorial Assistant

The views presented in the articles in...

Editorial Board

William Anderson, Boston University Moshe Ben-Akiva, Massachusetts Institute of Technology Kenneth Button, George Mason University Timothy Coburn, Abilene Christian University Mark Delucchi, University of California at Davis Antonio Esteve, U.S. Department of...

Loglinear Models and Goodness-of-Fit Statistics for Train Waybill Data

Herbert Lee* Duke University

Kert Viele University of Kentucky

Counts of carloads of train shipments are effectively described with loglinear models. This paper presents models of counts by...

Table 1 - Cross Validation Goodness-of-Fit Statistics for the Top Models

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Acknowledgements

Norman Y. Mineta Secretary

Michael P. Jackson Deputy Secretary

Ashish K. Sen Director

Richard R. Kowalewski Deputy Director

Susan J. Lapham Associate Director for...

Accounting for Uncertainty in Estimates of Total Traffic Volume: An Empirical Bayes Approach

Gary Davis* University of Minnesota

Shimin Yang The St. Paul Companies

Predicted or estimated totals of traffic volume over one or more years are required in both highway...

Table 2 - Evaluation of 90% Prediction Intervals: Second Factor Group

NOTE: Bolding indicates ATRs that have counts falling outside the credible bounds.

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Table 1 - Evaluation of 90% Prediction Intervals: First Factor Group

NOTE: Bolding indicates ATRs that have counts falling outside the credible bounds.

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Table 3 - Evaluation of 90% Prediction Intervals: Third Factor Group

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