Central limit theorem for supercritical Crump-Mode-Jagers processes counted with non-individual random characteristics
Abstract
Consider a supercritical Crump-Mode-Jagers process (Zt)t ≥ 0 counted with a random characteristic that depends on an individual's life and their descendant process up to a fixed generation. Under second moment assumptions, we establish a central limit theorem for Zt as t → ∞. Our result extends the recent work of Iksanov, Kolesko, and Meiners (2024) by relaxing their assumption of independent characteristics across individuals. We further demonstrate the applicability of our results to the study of fringe trees in several important random tree families, thereby providing insights into questions raised by Holmgren and Janson (2017).
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