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VeccTMVN  

Multivariate Normal Probabilities using Vecchia Approximation
View on CRAN: Click here


Download and install VeccTMVN package within the R console
Install from CRAN:
install.packages("VeccTMVN")

Install from Github:
library("remotes")
install_github("cran/VeccTMVN")

Install by package version:
library("remotes")
install_version("VeccTMVN", "1.3.1")



Attach the package and use:
library("VeccTMVN")
Maintained by
Jian Cao
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-01-26
Latest Update: 2025-07-14
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>.
How to cite:
Jian Cao (2024). VeccTMVN: Multivariate Normal Probabilities using Vecchia Approximation. R package version 1.3.1, https://cran.r-project.org/web/packages/VeccTMVN. Accessed 21 Aug. 2026.
Previous versions and publish date:
(2026-07-09 08:29), 1.0.0 (2024-01-26 12:30), 1.1.0 (2024-08-16 21:50), 1.1.1 (2024-09-05 01:00), 1.2.0 (2024-09-23 07:00), 1.2.1 (2024-11-26 20:40), 1.3.0 (2025-07-14 17:40), 1.3.1 (2025-08-19 08:20)
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Other R packages that VeccTMVN depends, imports, suggests or enhances
Complete documentation for VeccTMVN
Functions, R codes and Examples using the VeccTMVN R package
Full VeccTMVN package functions and examples
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