Lai presents a significant simulation of multivariate normal distribution. All of the bivariate distributions can be converted into one-dimensional integrals, and most cases of the trivariate normal distributions can be converted into one-dimensional integrals if the correlation coefficients ρ_ij = &lgr;_i &lgr;_j, | &lgr;_i | < 1, i = 1, 2, 3. For other problems, the author employs Genz’s transformation to develop Monte Carlo or quasi-Monte Carlo methods to estimate these distributions. The author applies this method to the case of discrete partial barrier options with a moving barrier. This novel technique can be useful in the application of weighted good lattice points rules to high-dimensional problems.