Stochastic Fixed Points and Nonlinear Perron-Frobenius Theorem
Abstract
We provide conditions for the existence of measurable solutions to the equation (Tω)=f(ω,(ω)), where T: → is an automorphism of the probability space and f(ω,·) is a strictly non-expansive mapping. We use results of this kind to establish a stochastic nonlinear analogue of the Perron-Frobenius theorem on eigenvalues and eigenvectors of a positive matrix. We consider a random mapping D(ω) of a random closed cone K(ω) in a finite-dimensional linear space into the cone K(Tω). Under assumptions of monotonicity and homogeneity of D(ω), we prove the existence of scalar and vector measurable functions α(ω)>0 and x(ω)∈ K(ω) satisfying the equation α(ω)x(Tω)=D(ω )x(ω) almost surely.
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