Multiple-drawing dynamic Friedman urns with opposite-reinforcement

Autor:	Shuyang Gao, Rafik Aguech
Rok vydání:	2023
Předmět:	Statistics and Probability Management Science and Operations Research Statistics Probability and Uncertainty Industrial and Manufacturing Engineering
Zdroj:	Probability in the Engineering and Informational Sciences. :1-15
ISSN:	1469-8951 0269-9648
DOI:	10.1017/s0269964822000535
Popis:	In this study, we consider a class of multiple-drawing opposite-reinforcing urns with time-dependent replacement rules. The class has the symmetric property of a Friedman-type urn. We divide the class into a small-increment regime and a large-increment regime. For small-increment schemes, we prove almost-sure convergence and a central limit theorem for the proportion of white balls by stochastic approximation. For large-increment schemes, by assuming the affinity condition, we show almost-sure convergence of the proportion of white balls by martingale theory and present a way to identify the limit distribution of the proportion of white balls.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::85b3e3b36a3920b2306ffbd0db24d772 https://doi.org/10.1017/s0269964822000535 Zobrazit plný text záznamu