Stochastic variational inequalities (SVI) model a large class of equilibrium problems subject to data uncertainty, and are closely related to stochastic optimization problems. The SVI solution is usually estimated by a solution to a sample average approximation (SAA) problem. This paper considers the normal map formulation of an SVI, and proposes a method to build asymptotically exact con dence regions and con dence intervals for the solution of the normal map formulation, based on the asymptotic distribution of SAA solutions. The con dence regions are single ellipsoids with high probability. We also discuss the computation of simultaneous and individual con dence intervals.
Citation
Department of Statistics and Operations Research, University of North Carolina at Chapel Hill