Laws of large numbers and central limit theorem for Ewens-Pitman model
Claudia Contardi, Emanuele Dolera, Stefano Favaro

TL;DR
This paper investigates the asymptotic behavior of the number of blocks in the Ewens-Pitman random partition when the model's parameter scales linearly with the sample size, establishing LLNs and CLTs in this regime.
Contribution
It extends the understanding of Ewens-Pitman partitions by analyzing the case where the parameter depends linearly on n, deriving new LLNs and CLTs for this non-standard asymptotic regime.
Findings
K_n scales as n under linear parameter growth
Established LLN and CLT for ; heta= n
Used Bernoulli and compound Poisson representations for proofs
Abstract
The Ewens-Pitman model is a distribution for random partitions of the set , with , indexed by parameters and , such that is the Ewens model in population genetics. The large asymptotic behaviour of the number of blocks in the Ewens-Pitman random partition has been extensively investigated in terms of almost-sure and Gaussian fluctuations, which show that scales as and depending on whether or , providing non-random and random limiting behaviours, respectively. In this paper, we study the large asymptotic behaviour of when the parameter is allowed to depend linearly on , a non-standard asymptotic regime first considered for in Feng (\textit{The Annals of Applied Probability}, \textbf{17}, 2007).…
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Taxonomy
TopicsComplex Systems and Time Series Analysis · Opinion Dynamics and Social Influence · Stochastic processes and statistical mechanics
