Stein's method for steady-state diffusion approximations of $M/Ph/n+M$ systems

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Stein's method for steady-state diffusion approximations: an introduction through the Erlang-A and Erlang-C models (2015, methodology): “ process decrease at a rate of 1/ √ R, where R is the oﬀered load. Futhermore, these error bounds are universal, valid in any load condition from lightly loaded to heavily loaded. 1. Introduction. In [10], the authors developed a framework based on Stein’s method [53, 54] to prove the rates of conve”
Approximation of stable law in Wasserstein-1 distance by Stein’s method (2017, methodology): “the convergencerateofPoissonapproximation[14]. Nowadays,Stein’smethodhasbeenextendedand reﬁned by many authors and has become a very important tool for getting bounds of measure 1 approximations, see [5, 9, 13, 21, 23, 28, 36, 43, 25, 26, 27, 32, 39, 40, 41, 44]. For more references, we refer the re”
Heavy traffic approximation for the stationary distribution of a generalized Jackson network: The BAR approach (2015, background): “In recent years, several papers [5, 6, 18, 20, 23] have gone beyond limit theorems, and establish rates of convergence to the approximating distribution.”