Taming Reluctant Random Walks in the Positive Quadrant
Jeremie Lumbroso, Marni Mishna, Yann Ponty
TL;DR
This paper introduces efficient methods for generating reluctant lattice walks in the positive quadrant, which are characterized by a strong drift towards the boundaries, addressing challenges in modeling such walks.
Contribution
It provides novel random generation strategies specifically designed for reluctant lattice walks with boundary drift.
Findings
Developed efficient algorithms for reluctant walk generation
Demonstrated improved performance over existing methods
Applicable to various boundary drift scenarios
Abstract
A lattice walk model is said to be reluctant if the defining step set has a strong drift towards the boundaries. We describe efficient random generation strategies for these walks.
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