A Probabilistic Model for the Multidimensional Scaling of Proximity and Preference Data

A probabilistic multidimensional scaling model that estimates both location and variance parameters for proximity and preference data is described and compared to a deterministic scaling model. Simulated and empirical choice data are used to compare models. Variance estimates from the probabilistic model are used to test a hypothesis about the homogeneity of stimulus perception under alternative modes of stimulus presentation.

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Year of publication:	1986
Authors:	MacKay, David B. ; Zinnes, Joseph L.
Published in:	Marketing Science. - Institute for Operations Research and the Management Sciences - INFORMS, ISSN 0732-2399. - Vol. 5.1986, 4, p. 325-344
Publisher:	Institute for Operations Research and the Management Sciences - INFORMS
Subject:	probabilistic model \| preference data \| proximity data \| multidimensional scaling

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Extent:	application/pdf
Type of publication:	Article
Other identifiers:	10.1287/mksc.5.4.325 [DOI]
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10008787511