000167876 001__ 167876
000167876 005__ 20180317094014.0
000167876 0247_ $$2doi$$a10.1016/j.trb.2012.11.002
000167876 02470 $$2ISI$$a000315319400004
000167876 037__ $$aPOST_TALK
000167876 245__ $$a Metropolis-Hastings sampling of paths
000167876 269__ $$a2011
000167876 260__ $$aOxford$$bPergamon-Elsevier Science Ltd$$c2011
000167876 300__ $$a14
000167876 336__ $$aTalks
000167876 520__ $$a We consider the previously unsolved problem of sampling paths according to a given distribution from a general network. The problem is difficult because of the combinatorial number of alternatives, which prohibits a complete enumeration of all paths and hence also forbids to compute the normalizing constant of the sampling distribution. The problem is important because the ability to sample from a known distribution introduces mathematical rigor into many applications, including the estimation of choice models with sampling of alternatives that can be formalized as paths in a decision network (most obviously route choice), probabilistic map matching, dynamic traffic assignment, and route guidance. (C) 2012 Elsevier Ltd. All rights reserved.
000167876 6531_ $$aPath sampling
000167876 6531_ $$aMetropolis Hastings
000167876 6531_ $$aSampling of alternatives in decision networks
000167876 700__ $$0243042$$aFlötteröd, Gunnar$$g188382
000167876 700__ $$0240563$$aBierlaire, Michel$$g118332
000167876 7112_ $$a International Choice Modeling Conference (ICMC)$$c Oulton Hall, Leeds$$dJuly 06, 2011
000167876 8564_ $$s432429$$uhttps://infoscience.epfl.ch/record/167876/files/FloeICMC2011.pdf$$yn/a$$zn/a
000167876 909CO $$ooai:infoscience.tind.io:167876$$pENAC$$ppresentation
000167876 909C0 $$0252123$$pTRANSP-OR$$xU11418
000167876 937__ $$aEPFL-TALK-167876
000167876 970__ $$aTALK-FloeICMC2011/TRANSP-OR
000167876 973__ $$aEPFL$$rREVIEWED$$sPUBLISHED
000167876 980__ $$aTALK