Convergence and simulation of centred kernel quadratic stochastic operators

Authors

  • K. Bartoszek Linköping University, SE-581 83, Linköping, Sweden https://orcid.org/0000-0002-5816-4345
  • M. Pułka Gdańsk University of Technology, 11/12 Narutowicza str., 80-233, Gdańsk, Poland
https://doi.org/10.15330/cmp.16.1.215-229

Keywords:

asymptotic stability, mixing nonlinear Markov process, nonhomogeneous Markov operator, quadratic stochastic operator, simulation
Published online: 2024-06-29

Abstract

In this work, we consider a class of centred kernel quadratic stochastic operators. We prove that in this class a centred kernel quadratic stochastic operator convergences almost surely and in $L^{2}$ with an exponential $L^{2}$-rate to its limit distribution. We propose an approximation scheme for this class of quadratic stochastic operators and describe three algorithms for simulating them. We consider in detail an example where the kernel is a Guassian one.

Article metrics
How to Cite
(1)
Bartoszek, K.; Pułka, M. Convergence and Simulation of Centred Kernel Quadratic Stochastic Operators. Carpathian Math. Publ. 2024, 16, 215-229.