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Some limit results for Markov chains indexed by trees (1406.3768v1)

Published 14 Jun 2014 in math.PR

Abstract: We consider a sequence of Markov chains $(\mathcal Xn)_{n=1,2,...}$ with $\mathcal Xn = (Xn_\sigma)_{\sigma\in\mathcal T}$, indexed by the full binary tree $\mathcal T = \mathcal T_0 \cup \mathcal T_1 \cup ...$, where $\mathcal T_k$ is the $k$th generation of $\mathcal T$. In addition, let $(\Sigma_k){k=0,1,2,...}$ be a random walk on $\mathcal T$ with $\Sigma_k \in \mathcal T_k$ and $\widetilde{\mathcal R}n = (\widetilde R_tn){t\geq 0}$ with $\widetilde R_tn := X_{\Sigma_{[tn]}}$, arising by observing the Markov chain $\mathcal Xn$ along the random walk. We present a law of large numbers concerning the empirical measure process $\widetilde{\mathcal Z}n = (\widetilde Z_tn)_{t\geq 0}$ where $\widetilde{Z}tn = \sum{\sigma\in\mathcal T_{[tn]}} \delta_{X_\sigman}$ as $n\to\infty$. Precisely, we show that if $\widetilde{\mathcal R}n \to \mathcal R$ for some Feller process $\mathcal R = (R_t){t\geq 0}$ with deterministic initial condition, then $\widetilde{\mathcal Z}n \to \mathcal Z$ with $Z_t = \delta{\mathcal L(R_t)}$.

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