Bayesian probit models for preference classification: an analysis of chess players’ propensity for risk-taking
Oelschläger L, Bauer D (2023)
In: Proceedings of the 37th International Workshop on Statistical Modelling. TU Dortmund University (Ed); 549-553.
Konferenzbeitrag
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Autor*in
herausgebende Körperschaft
TU Dortmund University
Abstract / Bemerkung
Probit models are widely used to analyze discrete choice behavior in fields such as transportation, marketing, and psychology. We propose a latent class model extension that allows for the classification of decider preferences. The model is estimated in a Bayesian framework, and the number of classes is determined by a Dirichlet process. In a simulation study, we verified that the dependence of the concentration prior diminishes as the number of deciders increases, resulting in stable inference. We further applied the proposed methodology in the context of chess, where chess players are classified according to three types of risk-taking propensity.
Erscheinungsjahr
2023
Titel des Konferenzbandes
Proceedings of the 37th International Workshop on Statistical Modelling
Seite(n)
549-553
ISBN
978-3-947323-42-5
Page URI
https://pub.uni-bielefeld.de/record/2984297
Zitieren
Oelschläger L, Bauer D. Bayesian probit models for preference classification: an analysis of chess players’ propensity for risk-taking. In: TU Dortmund University, ed. Proceedings of the 37th International Workshop on Statistical Modelling. 2023: 549-553.
Oelschläger, L., & Bauer, D. (2023). Bayesian probit models for preference classification: an analysis of chess players’ propensity for risk-taking. In TU Dortmund University (Ed.), Proceedings of the 37th International Workshop on Statistical Modelling (pp. 549-553).
Oelschläger, Lennart, and Bauer, Dietmar. 2023. “Bayesian probit models for preference classification: an analysis of chess players’ propensity for risk-taking”. In Proceedings of the 37th International Workshop on Statistical Modelling, ed. TU Dortmund University, 549-553.
Oelschläger, L., and Bauer, D. (2023). “Bayesian probit models for preference classification: an analysis of chess players’ propensity for risk-taking” in Proceedings of the 37th International Workshop on Statistical Modelling, TU Dortmund University ed. 549-553.
Oelschläger, L., & Bauer, D., 2023. Bayesian probit models for preference classification: an analysis of chess players’ propensity for risk-taking. In TU Dortmund University, ed. Proceedings of the 37th International Workshop on Statistical Modelling. pp. 549-553.
L. Oelschläger and D. Bauer, “Bayesian probit models for preference classification: an analysis of chess players’ propensity for risk-taking”, Proceedings of the 37th International Workshop on Statistical Modelling, TU Dortmund University, ed., 2023, pp.549-553.
Oelschläger, L., Bauer, D.: Bayesian probit models for preference classification: an analysis of chess players’ propensity for risk-taking. In: TU Dortmund University (ed.) Proceedings of the 37th International Workshop on Statistical Modelling. p. 549-553. (2023).
Oelschläger, Lennart, and Bauer, Dietmar. “Bayesian probit models for preference classification: an analysis of chess players’ propensity for risk-taking”. Proceedings of the 37th International Workshop on Statistical Modelling. Ed. TU Dortmund University. 2023. 549-553.
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Open Access