February 2023 Infinite-color randomly reinforced urns with dominant colors
Hristo Sariev, Sandra Fortini, Sonia Petrone
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Bernoulli 29(1): 132-152 (February 2023). DOI: 10.3150/21-BEJ1452

Abstract

We define and prove limit results for a class of dominant Pólya sequences, which are randomly reinforced urn processes with color-specific random weights and unbounded number of possible colors. Under fairly mild assumptions on the expected reinforcement, we show that the predictive and the empirical distributions converge almost surely (a.s.) in total variation to the same random probability measure P˜; moreover, P˜(D)=1 a.s., where D denotes the set of dominant colors for which the expected reinforcement is maximum. In the general case, the predictive probabilities and the empirical frequencies of any δ-neighborhood of D converge a.s. to one. That is, although non-dominant colors continue to be regularly observed, their distance to D converges in probability to zero. We refine the above results with rates of convergence. We further hint potential applications of dominant Pólya sequences in randomized clinical trials and species sampling, and use our central limit results for Bayesian inference.

Acknowledgments

The authors would like to thank the two anonymous referees for their careful reading and valuable comments. H. Sariev was partially supported by the Bulgarian Ministry of Education and Science under the National Research Programme “Young scientists and postdoctoral students” approved by DCM No. 577/17.08.2018.

Citation

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Hristo Sariev. Sandra Fortini. Sonia Petrone. "Infinite-color randomly reinforced urns with dominant colors." Bernoulli 29 (1) 132 - 152, February 2023. https://doi.org/10.3150/21-BEJ1452

Information

Received: 1 June 2021; Published: February 2023
First available in Project Euclid: 13 October 2022

MathSciNet: MR4497242
zbMATH: 1504.60037
Digital Object Identifier: 10.3150/21-BEJ1452

Keywords: Bayesian nonparametrics , Pólya sequences , random probability measures , Reinforced processes , Species sampling

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Vol.29 • No. 1 • February 2023
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