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Limit theorems and structural properties of the cat-and-mouse Markov chain and its generalisations

Part of: Markov processes Limit theorems

Published online by Cambridge University Press:  28 February 2022

Sergey Foss ,
Timofei Prasolov  and
Seva Shneer
Sergey Foss*
Affiliation:
Heriot-Watt University and Sobolev Institute of Mathematics
Timofei Prasolov*
Affiliation:
Novosibirsk State University
Seva Shneer*
Affiliation:
Heriot-Watt University and Novosibirsk State University
*
*Postal address: Heriot-Watt University, Edinburgh, EH14 4AS.
**Postal address: Pirogova 1, Novosibirsk State University, Novosibirsk, 630090.
*Postal address: Heriot-Watt University, Edinburgh, EH14 4AS.
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Abstract

We revisit the so-called cat-and-mouse Markov chain, studied earlier by Litvak and Robert (2012). This is a two-dimensional Markov chain on the lattice $\mathbb{Z}^2$, where the first component (the cat) is a simple random walk and the second component (the mouse) changes when the components meet. We obtain new results for two generalisations of the model. First, in the two-dimensional case we consider far more general jump distributions for the components and obtain a scaling limit for the second component. When we let the first component be a simple random walk again, we further generalise the jump distribution of the second component. Secondly, we consider chains of three and more dimensions, where we investigate structural properties of the model and find a limiting law for the last component.

Keywords

Cat-and-mouse gamesmultidimensional Markov chaincompound renewal processregular variationweak convergencerandomly stopped sums

MSC classification

Primary: 60J10: Markov chains (discrete-time Markov processes on discrete state spaces)
Secondary: 60F05: Central limit and other weak theorems

Information

Type
Original Article
Information
Advances in Applied Probability , Volume 54 , Issue 1 , March 2022 , pp. 141 - 166
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Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of Applied Probability Trust

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