Abstract
Construction of unimodal random probability measures on finite dimensional Euclidean space is considered. The approach based on Bayesian nonparametric models and Convexity Theory. Specifically, the proposed model makes use of the special properties of convex sets and Choquet’s theorem. As a result, we get random probability measures that admit derivatives almost everywhere in R d.
Mathematics Subject Classification (2000): Primary 62C10, 62G05
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Kouvaras, G., Kokolakis, G. (2011). Priors on the Space of Unimodal Probability Measures. In: Rassias, T., Brzdek, J. (eds) Functional Equations in Mathematical Analysis. Springer Optimization and Its Applications(), vol 52. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-0055-4_35
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DOI: https://doi.org/10.1007/978-1-4614-0055-4_35
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