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 gmail.com> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
yes |
| Materials: |
NEWS |
| CRAN checks: |
VeccTMVN results |
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