Journal of Transportation and Statistics
Journal of Transportation and Statistics Reviewers for Volume 4A B C D E F G H I J K L M N O P Q R S T U V W X Y Z
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1011
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Significant Regulatory Guidance
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Volume 4 Number 1 Back Cover
BTS | Volume 4 Number 1 - Back Cover Skip to content Volume 4 Number 1 Back Cover ContentsSandy 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
ContributorsDavid 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
Editorial BoardWilliam 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
Loglinear Models and Goodness-of-Fit Statistics for Train Waybill DataHerbert Lee* Duke University
Kert Viele University of Kentucky
AbstractCounts 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
Table 1 - Cross Validation Goodness-of-Fit Statistics for the Top ModelsExcel | CSV
Model RMSE F2 Full model 2029.2 6.59e+7 3.71e+9 All 2-way interactions 2118.2 9.28e+7 3.34e+9 No origin-destination interaction 4052.0 2.61e+8 3.81e+9 No origin-commodity interaction 4418.4...Acknowledgements
Acknowledgements U.S. Department of TransportationNorman Y. Mineta Secretary
Michael P. Jackson Deputy Secretary
Bureau of Transportation StatisticsAshish 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
Accounting for Uncertainty in Estimates of Total Traffic Volume: An Empirical Bayes ApproachGary Davis* University of Minnesota
Shimin Yang The St. Paul Companies
AbstractPredicted 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
Table 2 - Evaluation of 90% Prediction Intervals: Second Factor GroupNOTE: Bolding indicates ATRs that have counts falling outside the credible bounds.
Excel | CSV
Mn/DOT ATR number Fifth percentile of predictive distribution Log total count 95th percentile...Table 1 - Evaluation of 90% Prediction Intervals: First Factor Group
Table 1 - Evaluation of 90% Prediction Intervals: First Factor GroupNOTE: Bolding indicates ATRs that have counts falling outside the credible bounds.
Excel | CSV
Mn/DOT ATR number Fifth percentile of predictive distribution Log total count 95th percentile of...