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math.PR2018
Steady State Sensitivity Analysis of Continuous Time Markov Chains
Ting Wang, Petr Plechac
In this paper we study Monte Carlo estimators based on the likelihood ratio approach for steady-state sensitivity. We first extend the result of Glynn and Olvera-Cravioto [doi:doi:…
math.PR2015★ 1 cited
Path-space information bounds for uncertainty quantification and sensitivity analysis of stochastic dynamics
Paul Dupuis, Markos A. Katsoulakis, Yannis Pantazis +1
Uncertainty quantification is a primary challenge for reliable modeling and simulation of complex stochastic dynamics. Such problems are typically plagued with incomplete informati…