A Martingale Approach to Large-$\theta$ Ewens-Pitman Model

We investigate the asymptotic behavior of the number of parts $K_n$ in the Ewens–Pitman partition model under the regime where the diversity parameter is scaled linearly with the sample size, that is, $\theta =\lambda n$ for some~$\lambda >0$. While recent work has established a law of large numbers (LLN) and a central limit theorem (CLT) for $K_n$ in this regime, we revisit these results through a martingale-based approach. Our method yields significantly shorter proofs, and leads to sharper convergence rates in the CLT, including improved Berry–Esseen bounds in the case $\alpha =0$, and a new result for the regime $\alpha \in (0,1)$, filling a gap in the literature.