Choice set generation for iterated DTA simulations

We apply the Metropolis-Hastings algorithm to efficiently sample from arbitrary paths distributions in a general network. Paths can be generalized into all-day travel plans through, e.g., an appropriate network expansion. The Metropolis-Hastings algorithm creates a Markov chain of paths, which resembles DTA simulations that can also be phrased as Markov chains. A combination of both chains could lead to better understood DTA simulations that avoid the arbitrariness of current choice set generation procedures.


Presented at:
internal seminar, TU Berlin, Berlin, Germany, May 04, 2011
Year:
2011
Laboratories:




 Record created 2011-07-06, last modified 2018-01-28

External link:
Download fulltext
n/a
Rate this document:

Rate this document:
1
2
3
 
(Not yet reviewed)