New insights on the minimal random walk

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.

Introducing smooth amnesia to the memory of the Elephant Random Walk

“…Bercu and Laulin in [6] extended all the results of [3] to the multi-dimensional ERW (MERW) where d ≥ 1 and to its center of mass [7] using a martingale approach, while Bertenghi used the connection [8] to Pólya-type urns for the MERW. The ERW with stops or minimal RW, changing in particular the distribution of α n , has also been investigated [4,5,12,18]. The ERW with reinforced memory has been studied by Baur [2] via the urn approach, and Laulin [17] using martingales.…”

Introducing smooth amnesia to the memory of the Elephant Random Walk

“…Bercu and Laulin in [6] extended all the results of [3] to the multidimensional ERW (MERW) where d ≥ 1 and to its center of mass [7] using a martingale approach, while Bertenghi used the connection [8] to P ólya-type urns for the MERW. The ERW with stops or minimal RW, changing in particular the distribution of α n , has also been investigated [5,4,14,20]. The ERW with reinforced memory has been studied by Baur [1] via the urn approach, and Laulin [19] using martingales.…”