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The purpose of this paper is to investigate the asymptotic behavior of the multi-dimensional elephant random walk (MERW). It is a non-Markovian random walk which has a complete memory of its entire history. A wide range of literature is…

Probability · Mathematics 2017-09-22 Bernard Bercu , Lucile Laulin

In this paper, we explain the connection between the Elephant Random Walk (ERW) and an urn model \`a la P\'olya and derive functional limit theorems for the former. The ERW model was introduced by Sch\"utz and Trimper [2004] to study memory…

Statistical Mechanics · Physics 2020-01-07 Erich Baur , Jean Bertoin

In the simple random walk the steps are independent, viz., the walker has no memory. In contrast, in the Elephant Random walk (ERW), which was introduced by Sch\"utz and Trimper in 2004, the walker remembers the whole past, and the next…

Probability · Mathematics 2019-08-01 Allan Gut , Ulrich Stadtmüller

In the simple random walk the steps are independent, viz., the walker has no memory. In contrast, in the Elephant random walk(ERW), which was introduced by Schuetz and Trimper in 2004, the next step always depends on the whole path so far.…

Probability · Mathematics 2021-10-27 Allan Gut , Ulrich Stadtmüller

The purpose of this paper is to establish, via a martingale approach, some refinements on the asymptotic behavior of the one-dimensional elephant random walk (ERW). The asymptotic behavior of the ERW mainly depends on a memory parameter $p$…

Probability · Mathematics 2018-01-17 Bernard Bercu

The elephant random walk (ERW) is a microscopic, one-dimensional, discrete-time, non-Markovian random walk, which can lead to anomalous diffusion due to memory effects. In this study, I propose a multi-dimensional generalization in which…

Statistical Mechanics · Physics 2019-12-02 Vitor M. Marquioni

In this paper, we introduce the elephant random walk (ERW) with memory consisting of randomly selected steps from its history. It is a time-changed variant of the standard elephant random walk with memory consisting of its full history. At…

Probability · Mathematics 2025-01-23 M. Dhillon , K. K. Kataria

We study the so-called elephant random walk (ERW) which is a non-Markovian discrete-time random walk on $\mathbb{Z}$ with unbounded memory which exhibits a phase transition from diffusive to superdiffusive behaviour. We prove a law of large…

Statistical Mechanics · Physics 2017-06-07 Cristian F. Coletti , Renato Gava , Gunter M. Schütz

The Elephant Random Walk (ERW), first introduced by Sch\"utz and Trimper (2004), is a one-dimensional simple random walk on $ \mathbb{Z} $ having a memory about the whole past. We study the Shark Random Swim, a random walk whose steps are $…

Probability · Mathematics 2018-10-10 Silvia Businger

In this work, we discuss the smoothly amnesia-reinforced multidimensional elephant random walk (MARW). The scaling limit of the MARW is shown to exist in the diffusive, critical and superdiffusive regimes. We also establish the almost sure…

Probability · Mathematics 2023-01-23 Jiaming Chen , Lucile Laulin

In the simple random walk the steps are independent, whereas in the Elephant Random Walk (ERW), which was introduced by Sch\"utz and Trimper in 2004, the next step always depends on the whole path so far. In an earlier paper we investigated…

Probability · Mathematics 2020-05-20 Allan Gut , Ulrich Stadtmüller

We introduce a new random walk with unbounded memory obtained as a mixture of the Elephant Random Walk and the Dynamic Random Walk which we call the Dynamic Elephant Random Walk (DERW). As a consequence of this mixture the distribution of…

Probability · Mathematics 2021-02-04 Cristian F. Coletti , Lucas R. de Lima , Renato J. Gava , Denis A. Luiz

We consider a non-Markovian discrete-time random walk on $\mathbb{Z}$ with unbounded memory called the elephant random walk (ERW). We prove a strong invariance principle for the ERW. More specifically, we prove that, under a suitable…

Probability · Mathematics 2017-12-18 Cristian F. Coletti , Renato Gava , Gunter M. Schütz

The randomized play-the-winner rule (RPW) is a response-adaptive design proposed by Wei and Durham (1978) for sequentially randomizing patients to treatments in a two-treatment clinical trial so that more patients are assigned to the better…

Probability · Mathematics 2024-07-30 Li-Xin Zhang

This paper investigates functional limit theorems for the Elephant Random Walk (ERW) on general periodic structures, extending the Bertenghi's results on $\mathbb{Z}^d$. Our results reveal new structure-dependent quantities that do not…

Probability · Mathematics 2025-11-14 Shuhei Shibata

The goal of this paper is to investigate the asymptotic behavior of the multidimensional elephant random walk with stops (MERWS). In contrast with the standard elephant random walk, the elephant is allowed to stay on his own position. We…

Probability · Mathematics 2025-01-27 Bernard Bercu

This paper is devoted to the asymptotic analysis of the amnesic elephant random walk (AERW) using a martingale approach. More precisely, our analysis relies on asymptotic results for multidimensional martingales with matrix normalization.…

Probability · Mathematics 2022-04-25 Lucile Laulin

In the classical simple random walk the steps are independent, viz., the walker has no memory. In contrast, in the elephant random walk which was introduced by Sch\"utz and Trimper in 2004, the walker remembers the whole past, and the next…

Probability · Mathematics 2023-06-22 Allan Gut , Ulrich Stadtmüller

We introduce an original way to estimate the memory parameter of the elephant random walk, a fascinating discrete time random walk on integers having a complete memory of its entire history. Our estimator is nothing more than a…

Probability · Mathematics 2021-12-21 Bernard Bercu , Lucile Laulin

Gut and Stadm\"{u}ller (2021, 2022) initiated the study of the elephant random walk with limited memory. Aguech and El Machkouri (2024) published a paper in which they discuss an extension of results by Gut and Stadtm\"{u}ller (2022) for an…

Probability · Mathematics 2025-08-13 Rahul Roy , Masato Takei , Hideki Tanemura
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