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20072023
most citedMartingale proofs of many-server heavy-traffic limits for Markovian queues

160 citations · 298 across the 36 of their papers we have counts for

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Showing 2020Show all

7 papers · 1 filter

math.PR2020

Semimartingale properties of a generalized fractional Brownian motion and its mixtures with applications in asset pricing

Tomoyuki Ichiba, Guodong Pang, Murad S. Taqqu

We study the semimartingale properties for the generalized fractional Brownian motion (GFBM) introduced by Pang and Taqqu (2019) and discuss the applications of the GFBM and its mi…

math.PR2020★ 10 cited

Functional central limit theorems for epidemic models with varying infectivity

Guodong Pang, Etienne Pardoux

In this paper, we prove functional central limit theorems (FCLTs) for a stochastic epidemic model with varying infectivity and general infectious periods recently introduced in For…

math.PR2020

Path Properties of a Generalized Fractional Brownian Motion

Tomoyuki Ichiba, Guodong Pang, Murad S. Taqqu

The generalized fractional Brownian motion is a Gaussian self-similar process whose increments are not necessarily stationary. It appears in applications as the scaling limit of a…

math.PR2020

On system-wide safety staffing of large-scale parallel server networks

Hassan Hmedi, Ari Arapostathis, Guodong Pang

We introduce a "system-wide safety staffing" (SWSS) parameter for multiclass multi-pool networks of any tree topology, Markovian or non-Markovian, in the Halfin-Whitt regime. This…

math.PR2020

Epidemic models with varying infectivity

Raphael Forien, Guodong Pang, Etienne Pardoux

We introduce an epidemic model with varying infectivity and general exposed and infectious periods, where the infectivity of each individual is a random function of the elapsed tim…

math.PR2020★ 1 cited

Multi-patch epidemic models with general exposed and infectious periods

Guodong Pang, Etienne Pardoux

We study multi-patch epidemic models where individuals may migrate from one patch to another in either of the susceptible, exposed/latent, infectious and recovered states. We assum…