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Multivariate stochastic processes compatible with “aspect” models of similarity and choice

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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.

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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.

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

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Marley, A.A.J. Multivariate stochastic processes compatible with “aspect” models of similarity and choice. Psychometrika 46, 421–428 (1981). https://doi.org/10.1007/BF02293799

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  • DOI: https://doi.org/10.1007/BF02293799

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