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VeccTMVN

Multivariate Normal Probabilities using Vecchia Approximation

Under a different representation of the multivariate normal (MVN) probability, we can use the Vecchia approximation to sample the integrand at a linear complexity with respect to n. Additionally, both the SOV algorithm from Genz (92) and the exponential-tilting method from Botev (2017) can be adapted to linear complexity. The reference for the method implemented in this package is Jian Cao and Matthias Katzfuss (2024) "Linear-Cost Vecchia Approximation of Multivariate Normal Probabilities" <doi:10.48550/arXiv.2311.09426>. Two major references for the development of our method are Alan Genz (1992) "Numerical Computation of Multivariate Normal Probabilities" <doi:10.1080/10618600.1992.10477010> and Z. I. Botev (2017) "The Normal Law Under Linear Restrictions: Simulation and Estimation via Minimax Tilting" <doi:10.48550/arXiv.1603.04166>.

Versions across snapshots

VersionRepositoryFileSize
1.3.2 rolling linux/jammy R-4.5 VeccTMVN_1.3.2.tar.gz 243.0 KiB
1.3.2 rolling linux/noble R-4.5 VeccTMVN_1.3.2.tar.gz 246.3 KiB
1.3.2 rolling source/ R- VeccTMVN_1.3.2.tar.gz 38.5 KiB
1.3.2 latest linux/jammy R-4.5 VeccTMVN_1.3.2.tar.gz 243.0 KiB
1.3.2 latest linux/noble R-4.5 VeccTMVN_1.3.2.tar.gz 246.3 KiB
1.3.2 latest source/ R- VeccTMVN_1.3.2.tar.gz 38.5 KiB
1.3.2 2026-04-26 source/ R- VeccTMVN_1.3.2.tar.gz 38.5 KiB
1.3.2 2026-04-23 source/ R- VeccTMVN_1.3.2.tar.gz 38.5 KiB
1.3.2 2026-04-09 windows/windows R-4.5 VeccTMVN_1.3.2.zip 650.7 KiB
1.2.1 2025-04-20 source/ R- VeccTMVN_1.2.1.tar.gz 37.7 KiB

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