Geometric convergence rates for stochastically ordered Markov chains
Mathematics of Operations Research
Asymptotic Properties of Hybrid Diffusion Systems
SIAM Journal on Control and Optimization
Markov Chains and Stochastic Stability
Markov Chains and Stochastic Stability
IEEE Transactions on Information Theory
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In this paper, we consider a class of nonlinear autoregressive (AR) processes with state-dependent switching, which are two-component Markov processes. The state-dependent switching model is a nontrivial generalization of Markovian switching formulation and it includes the Markovian switching as a special case. We prove the Feller and strong Feller continuity by means of introducing auxiliary processes and making use of the Radon-Nikodym derivatives. Then, we investigate the geometric ergodicity by the Foster-Lyapunov inequality. Moreover, we establish the V-uniform ergodicity by means of introducing additional auxiliary processes and by virtue of constructing certain order-preserving couplings of the original as well as the auxiliary processes. In addition, illustrative examples are provided for demonstration.