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>.

Version: 1.0.0
Imports: Rcpp (≥ 1.0.10), Matrix (≥ 1.5-3), GpGp (≥ 0.4.0), truncnorm (≥ 1.0-8), GPvecchia, TruncatedNormal
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat (≥ 3.0.0), lhs, mvtnorm
Published: 2024-01-26
Author: Jian Cao [aut, cre], Matthias Katzfuss [aut]
Maintainer: Jian Cao <jcao2416 at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Materials: NEWS
CRAN checks: VeccTMVN results


Reference manual: VeccTMVN.pdf


Package source: VeccTMVN_1.0.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): VeccTMVN_1.0.0.tgz, r-oldrel (arm64): VeccTMVN_1.0.0.tgz, r-release (x86_64): VeccTMVN_1.0.0.tgz


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