Sensitivity error bounds for non-exponential stochastic networks
Error bounds for arbitrary approximations of “nearly reversible” Markov chains and a communications example
Time-discretization for controlled Markov processes. II. A jump and diffusion application
Time-discretization for controlled Markov processes. I. General approximation results
Monotonicity and comparison results for nonnegative dynamic systems. Part II: Continuous-time case
This second Part II, which follows a first Part I for the discrete-time case (see [DijkSl1]), deals with monotonicity and comparison results, as generalization of the pure stochastic case, for stochastic dynamic systems with arbitrary nonnegative generators in the continuous-time case. In contrast with the discrete-time case the generalization is no longer straightforward. A discrete-time transformation will therefore be developed first. Next, results from Part I can be adopted. The conditions,...
Monotonicity and comparison results for nonnegative dynamic systems. Part I: Discrete-time case
In two subsequent parts, Part I and II, monotonicity and comparison results will be studied, as generalization of the pure stochastic case, for arbitrary dynamic systems governed by nonnegative matrices. Part I covers the discrete-time and Part II the continuous-time case. The research has initially been motivated by a reliability application contained in Part II. In the present Part I it is shown that monotonicity and comparison results, as known for Markov chains, do carry over rather smoothly...
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