Evaluation of Multivariate Normal Probability Integrals using a Low Variance Simulator
提出一种低方差模拟器，通过因子分析协方差结构精确计算初始点积分，并利用Plackett恒等式评估线积分，在十维及以下问题中比GHK模拟器精度高一个到两个数量级。
This paper describes a low variance simulator of the normal distribution function. The probability integral is evaluated exactly at an initial point specified with a factor analytic covariance structure, so that the integral can be derived using dimension reduction techniques. The line integral between the initial point and the desired point is evaluated using Plackett's identity. A Monte Carlo simulation of this line integral simulator (LIS) with the Geweke-Hajivassiliou-Keane (GHK) simulator demonstrates that for dimensions of ten or less, the LIS outperformed the GHK simulator, typically by an order of magnitude and in some cases by two orders of magnitude. Copyright 1994 by MIT Press.