000167876 001__ 167876
000167876 005__ 20190316235158.0
000167876 0247_ $$2doi$$a10.1016/j.trb.2012.11.002
000167876 02470 $$2ISI$$a000315319400004
000167876 037__ $$aPOST_TALK
000167876 245__ $$aMetropolis-Hastings sampling of paths
000167876 269__ $$a2011
000167876 260__ $$bPergamon-Elsevier Science Ltd$$c2011$$aOxford
000167876 300__ $$a14
000167876 336__ $$aTalks
000167876 520__ $$aWe consider the previously unsolved problem of sampling paths according to a given distribution from a general network. The problem is difficult because of the combinatorial number of alternatives, which prohibits a complete enumeration of all paths and hence also forbids to compute the normalizing constant of the sampling distribution. The problem is important because the ability to sample from a known distribution introduces mathematical rigor into many applications, including the estimation of choice models with sampling of alternatives that can be formalized as paths in a decision network (most obviously route choice), probabilistic map matching, dynamic traffic assignment, and route guidance. (C) 2012 Elsevier Ltd. All rights reserved.
000167876 6531_ $$aPath sampling
000167876 6531_ $$aMetropolis Hastings
000167876 6531_ $$aSampling of alternatives in decision networks
000167876 700__ $$0243042$$g188382$$aFlötteröd, Gunnar
000167876 700__ $$aBierlaire, Michel$$g118332$$0240563
000167876 7112_ $$dJuly 06, 2011$$cOulton Hall, Leeds$$aInternational Choice Modeling Conference (ICMC)
000167876 8564_ $$uhttps://infoscience.epfl.ch/record/167876/files/FloeICMC2011.pdf$$zn/a$$s432429$$yn/a
000167876 909C0 $$xU11418$$0252123$$pTRANSP-OR
000167876 909CO $$qGLOBAL_SET$$ppresentation$$ooai:infoscience.tind.io:167876$$pENAC
000167876 937__ $$aEPFL-TALK-167876
000167876 970__ $$aTALK-FloeICMC2011/TRANSP-OR
000167876 973__ $$rREVIEWED$$sPUBLISHED$$aEPFL
000167876 980__ $$aTALK