New insights on the minimal random walk
arXiv:2112.09321 · doi:10.1088/1751-8121/ac92ad
Abstract
The aim of this paper is to deepen the analysis of the asymptotic behavior of the so-called minimal random walk (MRW) using a new martingale approach. The MRW is a discrete-time random walk with infinite memory that has three regimes depending on the location of its two parameters. In the diffusive and critical regimes, we establish new results on the almost sure asymptotic behavior of the MRW, such as the quadratic strong law and the law of the iterated logarithm. In the superdiffusive regime, we prove the almost sure convergence of the MRW, properly normalized, to a nondegenerate random variable. Moreover, we show that the fluctuation of the MRW around its limiting random variable is still Gaussian.
References in corpus (8)
- Elephants can always remember: Exact long-range memory effects in a non-Markovian random walk
- Elephant Random Walks and their connection to Pólya-type urns
- A martingale approach for the elephant random walk
- Central Limit Theorem for the Elephant Random Walk
- A strong invariance principle for the elephant random walk
- Gaussian fluctuation for superdiffusive elephant random walks
- Limit theorems for the 'laziest' minimal random walk model of elephant type
- Limit theorems for a minimal random walk model