Bayesian flexible modeling of trip durations

Hugh Chipman, Edward George, Jason Lemp and Robert McCulloch

Transportation Research Part B: Methodological, 2010, vol. 44, issue 5, 686-698

Abstract: Recent advances in Bayesian modeling have led to stunning improvements in our ability to flexibly and easily model complex high-dimensional data. Flexibility comes from the use of a very large number of parameters without fixed dimension. Priors are placed on the parameters to avoid over-fitting and sensibly guide the search in model space for appropriate data-driven model choice. Modern computational, high dimensional search methods (in particular Markov Chain Monte Carlo) then allow us to search the parameter space. This paper introduces the application of BART, Bayesian Additive Regression Trees, to modelling trip durations. We have survey data on characteristics of trips in the Austin area. We seek to relate the trip duration to features of the household and trip characteristics. BART enables one to make inferences about the relationship with minimal assumptions and user decisions.

Keywords: Markov; Chain; Monte; Carlo; Boosting; Ensemble; modeling (search for similar items in EconPapers)
Date: 2010
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0191-2615(10)00015-9
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:transb:v:44:y:2010:i:5:p:686-698

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

Access Statistics for this article

Transportation Research Part B: Methodological is currently edited by Fred Mannering

More articles in Transportation Research Part B: Methodological from Elsevier
Bibliographic data for series maintained by Catherine Liu ().