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December 2012 Dynamical functional prediction and classification, with application to traffic flow prediction
Jeng-Min Chiou
Ann. Appl. Stat. 6(4): 1588-1614 (December 2012). DOI: 10.1214/12-AOAS595

Abstract

Motivated by the need for accurate traffic flow prediction in transportation management, we propose a functional data method to analyze traffic flow patterns and predict future traffic flow. In this study we approach the problem by sampling traffic flow trajectories from a mixture of stochastic processes. The proposed functional mixture prediction approach combines functional prediction with probabilistic functional classification to take distinct traffic flow patterns into account. The probabilistic classification procedure, which incorporates functional clustering and discrimination, hinges on subspace projection. The proposed methods not only assist in predicting traffic flow trajectories, but also identify distinct patterns in daily traffic flow of typical temporal trends and variabilities. The proposed methodology is widely applicable in analysis and prediction of longitudinally recorded functional data.

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Jeng-Min Chiou. "Dynamical functional prediction and classification, with application to traffic flow prediction." Ann. Appl. Stat. 6 (4) 1588 - 1614, December 2012. https://doi.org/10.1214/12-AOAS595

Information

Published: December 2012
First available in Project Euclid: 27 December 2012

zbMATH: 1257.62090
MathSciNet: MR3058676
Digital Object Identifier: 10.1214/12-AOAS595

Keywords: clustering , discrimination , functional regression , intelligent transportation system , mixture model , subspace projection , traffic flow rate

Rights: Copyright © 2012 Institute of Mathematical Statistics

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Vol.6 • No. 4 • December 2012
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