Right-most position of a last progeny modified time inhomogeneous branching random walk

Antar Bandyopadhyay and Partha Pratim Ghosh

Statistics & Probability Letters, 2023, vol. 193, issue C

Abstract: In this work, we consider a modification of the time inhomogeneous branching random walk, where the driving increment distribution changes over time macroscopically. Following Bandyopadhyay and Ghosh (2021), we give certain independent and identically distributed (i.i.d.) displacements to all the particles at the last generation. We call this process last progeny modified time inhomogeneous branching random walk (LPMTI-BRW). Under very minimal assumptions on the underlying point processes of the displacements, we show that the maximum displacement converges to a non-trivial limit after an appropriate centering which is either linear or linear with a logarithmic correction. Interestingly, the limiting distribution depends only on the first set of increments. We also derive Brunet–Derrida-type results of point process convergence of our LPMTI-BRW to a decorated Poisson point process. As in the case of the maximum, the limiting point process also depends only on the first set of increments. Our proofs are based on a method of coupling the maximum displacement with an appropriate linear statistics, which was introduced by Bandyopadhyay and Ghosh (2021).

Keywords: Branching random walk; Time inhomogeneous environments; Maximum operator; Smoothing transformation; Decorated Poisson point process (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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DOI: 10.1016/j.spl.2022.109697

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