Computation Of Multivariate Normal Probabilities Using Bivariate Conditioning With Simulation

Download or read book Computation of Multivariate Normal Probabilities Using Bivariate Conditioning with Simulation written by Giang B. Trinh and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We introduce algorithms for block LDLt decompositions of positive definite covariance matrices. These are extensions of the LDLt decomposition which requires D to be a diagonal matrix. We make use of these algorithms to represent the mutivariate normal (MVN) probability as a bivariate-iterated, trivariate-iterated and multivariate-iterated integrals. From there, we introduce a new method of approximating and simulating MVN probabilities using bivariate conditioning with simulation. Basic algorithms for bivariate, trivariate, multivariate conditioning are derived. A new approximate formula for multivariate normal probabilities which uses a product of bivariate normal probabilities is derived and considered with different variance reduction techniques. The new method is compared with approximation methods based on products of univariate normal probabilities. The new method uses conditioning with a sequence of truncated bivariate probabilities. Simulation methods which use Monte Carlo, and quasi-Monte Carlo point sets are developed.