Metropolis–Hastings sampling of paths

Metropolis–Hastings sampling of paths

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Article ID: iaor20131303
Volume: 48
Start Page Number: 53
End Page Number: 66
Publication Date: Feb 2013
Journal: Transportation Research Part B
Authors: ,
Keywords: networks: path, statistics: distributions
Abstract:

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.

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