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math.PR2019
A Many-Server Functional Strong Law For A Non-Stationary Loss Model
Prakash Chakraborty, Harsha Honnappa
The purpose of this note is to show that it is possible to establish a many-server functional strong law of large numbers (FSLLN) for the fraction of occupied servers (i.e., the sc…
math.PR2019
Strong Embeddings for Transitory Queueing Models
Prakash Chakraborty, Harsha Honnappa
In this paper we establish strong embedding theorems, in the sense of the Komlos-Major-Tusnady framework, for the performance metrics of a general class of transitory queueing mode…
math.PR2019
Large Deviations of Bivariate Gaussian Extrema
Remco van der Hofstad, Harsha Honnappa
We establish sharp tail asymptotics for component-wise extreme values of bivariate Gaussian random vectors with arbitrary correlation between the components. We consider two scalin…