An Exponential-Family Multidimensional Scaling Mixture Methodology

Michel Wedel and Wayne S DeSarbo

Journal of Business & Economic Statistics, 1996, vol. 14, issue 4, 447-59

Abstract: A multidimensional scaling methodology (STUNMIX) for the analysis of subjects preference/choice of stimuli is presented, which integrates previous models into a single framework. Locations of the stimuli and the ideal-points of derived segments of subjects on latent dimensions are estimated simultaneously. The methodology is formulated in the framework of the exponential family of distributions. Possible reparametrizations of stimulus coordinates by stimulus characteristics, as well as of probabilities of segment membership by subject background variables, are permitted. The models are estimated in a maximum likelihood framework.

Date: 1996
References: Add references at CitEc
Citations: View citations in EconPapers (14)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

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:bes:jnlbes:v:14:y:1996:i:4:p:447-59

Ordering information: This journal article can be ordered from
http://www.amstat.org/publications/index.html

Access Statistics for this article

Journal of Business & Economic Statistics is currently edited by Jonathan H. Wright and Keisuke Hirano

More articles in Journal of Business & Economic Statistics from American Statistical Association
Bibliographic data for series maintained by Christopher F. Baum ().