A note on alternative matrix entry estimation techniques

Sue McNeil and Chris Hendrickson

Transportation Research Part B: Methodological, 1985, vol. 19, issue 6, 509-519

Abstract: Estimation of trip tables and other matrices that are subject to constraints is a common practical problem. This note reviews four common estimation methods: (1) minimization of the sum of absolute deviations, (2) the biproportional technique, (3) information minimization and (4) constrained generalized least squares (CGLS) regression. A small example illustrates their application. Computational approaches and burdens as well as implicit error structure assumptions are reviewed. The paper concludes that estimates obtained from the biproportional, information minimization and CGLS regression (with a chi-square type error distribution assumption), are likely to be similar in practice. Choice of an appropriate technique depends upon a priori assumptions of error structures, relative computational burdens and the usefulness of estimate uncertainty measures.

Date: 1985
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/0191-2615(85)90045-1
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:19:y:1985:i:6:p:509-519

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 ().