Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Okabe, Yasunori, Mano, Hajime, Itoh, Yoshiaki
Format: Preprint
Veröffentlicht: 2025
Schlagworte:
Online-Zugang:https://arxiv.org/abs/2507.00362
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
_version_ 1866913920055246848
author Okabe, Yasunori
Mano, Hajime
Itoh, Yoshiaki
author_facet Okabe, Yasunori
Mano, Hajime
Itoh, Yoshiaki
contents This paper treats a random collision model of three species, which is represented by the random time change of three standard Poisson processes. The prey-predator relation in the random collision model looks like paper-scissors-stone game, and the model is called the paper-scissors model. At first, we investigate the stochastic structure of our model. By using stochastic calculus, the model is decomposed into a semi-martingale, and we prove a weak law of large numbers and a central limit theorem. The main purpose of this paper is to obtain an ordinary differential equation from the weak law and a stochastic differential equation from the central limit theorem.
format Preprint
id arxiv_https___arxiv_org_abs_2507_00362
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Paper-Scissors-Stone Model for Interacting Population and its Limit Theorem
Okabe, Yasunori
Mano, Hajime
Itoh, Yoshiaki
Probability
This paper treats a random collision model of three species, which is represented by the random time change of three standard Poisson processes. The prey-predator relation in the random collision model looks like paper-scissors-stone game, and the model is called the paper-scissors model. At first, we investigate the stochastic structure of our model. By using stochastic calculus, the model is decomposed into a semi-martingale, and we prove a weak law of large numbers and a central limit theorem. The main purpose of this paper is to obtain an ordinary differential equation from the weak law and a stochastic differential equation from the central limit theorem.
title Paper-Scissors-Stone Model for Interacting Population and its Limit Theorem
topic Probability
url https://arxiv.org/abs/2507.00362