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VeccTMVN

Multivariate Normal Probabilities using Vecchia Approximation

v1.3.2 · Feb 3, 2026 · GPL (>= 2)

Description

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>.

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OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026

Reverse Dependencies (1)

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Dependency Network

Dependencies Reverse dependencies Rcpp Matrix GpGp truncnorm GPvecchia TruncatedNormal nleqslv gctsc VeccTMVN

Version History

new 1.3.2 Mar 10, 2026