White Rose University Consortium logo
University of Leeds logo University of Sheffield logo York University logo

Using Non-Parametric Tests to Evaluate Traffic Forecasting Performance.

Clark, S.D., Grant-Muller, S.M. and Chen, H. (2002) Using Non-Parametric Tests to Evaluate Traffic Forecasting Performance. Journal of Transportation and Statistics, 5 (1). pp. 47-56.

Full text available as:
[img]
Preview
Text
ITS2206-Using_Nonparametric__uploadable.pdf
Available under License : See the attached licence file.

Download (277Kb)

Abstract

This paper proposes the use of a number of nonparametric comparison methods for evaluating traffic flow forecasting techniques. The advantage to these methods is that they are free of any distributional assumptions and can be legitimately used on small datasets. To demonstrate the applicability of these tests, a number of models for the forecasting of traffic flows are developed. The one-step-ahead forecasts produced are then assessed using nonparametric methods. Consideration is given as to whether a method is universally good or good at reproducing a particular aspect of the original series. That choice will be dictated, to a degree, by the user’s purpose for assessing traffic flow.

Item Type: Article
Copyright, Publisher and Additional Information: This is a publisher produced version of a paper published in the Journal of Transportation and Statistics. The papers from this journal are in the public domain and may be used and reprinted without special permission. For more information please visit their website.
Academic Units: The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds)
Depositing User: Adrian May
Date Deposited: 28 Jun 2007
Last Modified: 08 Feb 2013 17:04
Published Version: http://www.bts.gov/publications/journal_of_transpo...
Status: Published
Publisher: Bureau of Transportation Statistics
Refereed: Yes
URI: http://eprints.whiterose.ac.uk/id/eprint/2541

Actions (login required)

View Item View Item