Fast computation of high-dimensional multivariate normal probabilities
A new efficient method is proposed to compute multivariate normal probabilities over rectangles in high dimensions. The method exploits four variance reduction techniques: conditional Monte Carlo, importance sampling, splitting and control variates. Simulation results are presented that evaluate the performance of the new proposed method. The new method is designed for computing small exceedance probabilities.
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