Numerical Computation of Multivariate Normal Probabilities Using Bivariate Conditioning

DOI10.1007/978-3-319-33507-0_13zbMath1356.65026OpenAlexW2492168629MaRDI QIDQ2957037

Giang Trinh, A. C. Genz

Publication date: 20 January 2017

Published in: Springer Proceedings in Mathematics & Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-319-33507-0_13

zbMATH Keywords

algorithmquasi-Monte Carlomultivariate normal probabilitiesbivariate conditioning

Mathematics Subject Classification ID

Related Items (1)

Quantitative Verification for Neural Networks using ProbStars

Uses Software

• AS 195

Cites Work

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• Bivariate conditioning approximations for multivariate normal probabilities
• Fast simulation of truncated Gaussian distributions
• Computation of multivariate normal and \(t\) probabilities
• Smoothness and dimension reduction in quasi-Monte Carlo methods
• Improving the rejection sampling method in quasi-Monte Carlo methods
• Alternative sampling methods for estimating multivariate normal probabilities
• Discrepancy bounds for deterministic acceptance-rejection samplers
• Fast algorithms for component-by-component construction of rank-1 lattice rules in shift-invariant reproducing kernel Hilbert spaces
• The Efficient Generation of Random Orthogonal Matrices with an Application to Condition Estimators
• Moments of the censored and truncated bivariate normal distribution

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