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This is a Quantitative Study study.

October 7, 2025Open Access

Bayesian nonparametric inference on a Fr\'echet class

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Bayesian nonparametric methods can construct probability measures on a Fréchet class, enhancing inference techniques.
The evaluation of conditional distributions reinforces the relationship between prior and posterior distributions in Bayesian inference.
The work extends to develop priors on different probability measure sets, thus broadening the scope of Bayesian methodologies.
Using exchangeable random variables, the study clarifies the role of the de Finetti measure in Bayesian frameworks.

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The study demonstrates how to develop probability measures in Bayesian nonparametrics, indicating properties of prior and posterior distributions.

Dreassi et al. (2025) studied this question.

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The study demonstrates how to develop probability measures in Bayesian nonparametrics, indicating properties of prior and posterior distributions.