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Multivariate Stochastic Processes Compatible with “Aspect” Models of Similarity and Choice

Published online by Cambridge University Press:  01 January 2025

A. A. J. Marley
A. A. J. Marley*
Affiliation:
Department of Psychology McGill University
*
Requests for reprints should be addressed to A.A.J.Marley, Dept. of Psychology, McGill University, 1205 Avenue Dr. Penfield, Montreal, Quebec, H3A 1B1, Canada.
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Abstract

Various recent works have developed “feature” or “aspect” models of similarity and preference. These models are more concerned with the fine detail of the judgment process than were prior models, but nevertheless they have not in general developed an underlying stochastic process compatible with the assumed structure. In this paper, we show that a particular class of multivariate stochastic processes, namely those associated with the Marshall-Olkin multivariate exponential distribution, generates several of these models. In particular, such stochastic processes (appropriately interpreted) yield Tversky's elimination by aspects model, Edgell and Geisler's (normal) additive random aspects model, and Shepard and Arabie's additive cluster model.

Keywords

choicesimilaritypreferencestochastic models
Type
Original Paper
Information
Psychometrika , Volume 46 , Issue 4 , December 1981 , pp. 421 - 428
Copyright
Copyright © 1981 The Psychometric Society

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Footnotes

This work was supported by Natural Science and Engineering Research Council of Canada Grant A8124 to A.A.J. Marley.

References

Reference Note

Marley, A. A. J. The compatibility between random utility models of choice and competing causes models of reaction time. Manuscript, Department of Psychology, McGill University, 1976.Google Scholar

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