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1 - Introduction

Published online by Cambridge University Press:  02 February 2017

Mikhail Menshikov
Affiliation:
University of Durham
Serguei Popov
Affiliation:
Universidade Estadual de Campinas, Brazil
Andrew Wade
Affiliation:
University of Durham
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Summary

RandomWalks

Random walks are fundamental models in probability theory that exhibit deep mathematical properties and enjoy broad application across the sciences and beyond. Generally speaking, a random walk is a stochastic process modelling the random motion of a particle (or random walker) in space. The particle's trajectory is described by a series of random increments or jumps at discrete instants in time. Central questions for these models involve the long-time asymptotic behaviour of the walker.

Random walks have a rich history involving several disciplines. Classical one-dimensional random walks were first studied several hundred years ago as models for games of chance, such as the so-called gambler's ruin problem. Similar reasoning led to random walk models of stock prices described by Jules Regnault in his 1863 book [265] and Louis Bachelier in his 1900 thesis [14]. Many-dimensional random walks were first studied at around the same time, arising from the work of pioneers of science in diverse applications such as acoustics (Lord Rayleigh's theory of sound developed from about 1880 [264]), biology (Karl Pearson's 1906 [254] theory of random migration of species), and statistical physics (Einstein's theory of Brownian motion developed during 1905–8 [86]). The mathematical importance of the random walk problem became clear after Pόlya's work in the 1920s, and over the last 60 years or so there have emerged beautiful connections linking random walk theory and other influential areas of mathematics, such as harmonic analysis, potential theory, combinatorics, and spectral theory. Random walk models have continued to find new and important applications in many highly active domains of modern science: see for example the wide range of articles in [287]. Specific recent developments include modelling of microbe locomotion in microbiology [23, 245], polymer conformation in molecular chemistry [15, 202], and financial systems in economics.

Spatially homogeneous random walks are the subject of a substantial literature, including [139, 195, 269, 293]. In many modelling applications, the classical assumption of spatial homogeneity is not realistic: the behaviour of the random walker may depend on the present location in space.

Type
Chapter
Information
Non-homogeneous Random Walks
Lyapunov Function Methods for Near-Critical Stochastic Systems
, pp. 1 - 20
Publisher: Cambridge University Press
Print publication year: 2016

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  • Introduction
  • Mikhail Menshikov, University of Durham, Serguei Popov, Universidade Estadual de Campinas, Brazil, Andrew Wade, University of Durham
  • Book: Non-homogeneous Random Walks
  • Online publication: 02 February 2017
  • Chapter DOI: https://doi.org/10.1017/9781139208468.003
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  • Introduction
  • Mikhail Menshikov, University of Durham, Serguei Popov, Universidade Estadual de Campinas, Brazil, Andrew Wade, University of Durham
  • Book: Non-homogeneous Random Walks
  • Online publication: 02 February 2017
  • Chapter DOI: https://doi.org/10.1017/9781139208468.003
Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • Introduction
  • Mikhail Menshikov, University of Durham, Serguei Popov, Universidade Estadual de Campinas, Brazil, Andrew Wade, University of Durham
  • Book: Non-homogeneous Random Walks
  • Online publication: 02 February 2017
  • Chapter DOI: https://doi.org/10.1017/9781139208468.003
Available formats
×