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Persistence of AR($1$) sequences with Rademacher innovations and linear mod $1$ transforms

Published online by Cambridge University Press:  07 April 2026

VLADISLAV VYSOTSKY*
Affiliation:
Department of Mathematics, University of Sussex , Brighton, UK
VITALI WACHTEL
Affiliation:
Bielefeld University , Bielefeld, Germany (e-mail: wachtel@math.uni-bielefeld.de)
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Abstract

We study the probability that an AR(1) Markov chain $X_{n+1}=aX_n+\xi _{n+1}$, where $a\in (0,1)$ is a constant, stays non-negative for a long time. We find the exact asymptotics of this probability and the weak limit of $X_n$ conditioned to stay non-negative, assuming that the independent and identically distributed innovations $\xi _n$ take only two values $\pm 1$ and $a \le \tfrac 23$. This limiting distribution is quasi-stationary. It has no atoms and is singular with respect to the Lebesgue measure when $\tfrac 12< a \le \tfrac 23$, except for the case when $a=\tfrac 23$ and $\mathbb P(\xi _n=1)=\tfrac 12$, where this distribution is uniform on the interval $[0,3]$. This is similar to the properties of Bernoulli convolutions. For $0 < a \le \tfrac 12$, the situation is much simpler and the limiting distribution is a $\delta $-measure. To prove these results, we uncover a close connection between $X_n$ killed at exiting $[0, \infty )$ and the classical dynamical system defined by the piecewise linear mapping $x \mapsto x/a + 1/2\ \pmod 1$. Namely, the trajectory of this system started at $X_n$ deterministically recovers the values of the killed chain in reversed time. We use this fact to construct a suitable Banach space, where the transition operator of the killed chain has the compactness properties that allow us to apply a conventional argument of the Perron–Frobenius type.

Information

Type
Original Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2026. Published by Cambridge University Press
Figure 0

Figure 1 The graphs of $\unicode{x3bb} _a(p)$ for fixed p.

Figure 1

Figure 2 The graph of $\varkappa _a'$.

Figure 2

Figure 3 The distribution functions of $\nu _a$ for $p=0.3$, $p=0.5$, $p=0.7$ (top to bottom plots in all four subfigures), where (a) a = 0.55, (b) a = 0.6, (c) a = 0.65, and (d) a = $\tfrac{2}{3}$.