Stein's method for steady-state diffusion approximations: an introduction through the Erlang-A and Erlang-C models

  title={Stein's method for steady-state diffusion approximations: an introduction through the Erlang-A and Erlang-C models},
  author={Anton Braverman and J. Dai and Jiekun Feng},
  journal={arXiv: Probability},
  • Anton Braverman, J. Dai, Jiekun Feng
  • Published 2015
  • Mathematics
  • arXiv: Probability
  • This paper provides an introduction to the Stein method framework in the context of steady-state diffusion approximations. The framework consists of three components: the Poisson equation and gradient bounds, generator coupling, and moment bounds. Working in the setting of the Erlang-A and Erlang-C models, we prove that both Wasserstein and Kolmogorov distances between the stationary distribution of a normalized customer count process, and that of an appropriately defined diffusion process… CONTINUE READING
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