English

One-dimensional infinite memory imitation models with noise

Probability 2015-08-05 v1

Abstract

In this paper we study stochastic process indexed by Z\mathbb {Z} constructed from certain transition kernels depending on the whole past. These kernels prescribe that, at any time, the current state is selected by looking only at a previous random instant. We characterize uniqueness in terms of simple concepts concerning families of stochastic matrices, generalizing the results previously obtained in De Santis and Piccioni (J. Stat. Phys., 150(6):1017--1029, 2013).

Keywords

Cite

@article{arxiv.1508.00867,
  title  = {One-dimensional infinite memory imitation models with noise},
  author = {Emilio De Santis and Mauro Piccioni},
  journal= {arXiv preprint arXiv:1508.00867},
  year   = {2015}
}

Comments

22 pages, 3 figures

R2 v1 2026-06-22T10:26:24.397Z