Metropolis-Hastings sampling of paths

• Presented at: International Choice Modeling Conference (ICMC), Oulton Hall, Leeds, July 06, 2011
• Oxford: Pergamon-Elsevier Science Ltd, 2011

We consider the previously unsolved problem of sampling paths according to a given distribution from a general network. The problem is difficult because of the combinatorial number of alternatives, which prohibits a complete enumeration of all paths and hence also forbids to compute the normalizing constant of the sampling distribution. The problem is important because the ability to sample from a known distribution introduces mathematical rigor into many applications, including the estimation of choice models with sampling of alternatives that can be formalized as paths in a decision network (most obviously route choice), probabilistic map matching, dynamic traffic assignment, and route guidance. (C) 2012 Elsevier Ltd. All rights reserved.

Keywords: Path sampling ; Metropolis Hastings ; Sampling of alternatives in decision networks

Reference

• EPFL-TALK-167876
• doi:10.1016/j.trb.2012.11.002
• View record in Web of Science

Record created on 2011-08-11, modified on 2017-02-16