GenzBretz

TLRQMC

an integer, specifying the number of per-batch Monte Carlo samples. The 
 total number of Monte Carlo samples is 20 X N

an integer, specifying the block size for the tile-low-rank methods

numeric value, specifying the truncation level for the tile-low-rank methods

epsl

The two functions return objects containing the parameters for the dense-matrix based Quasi-Monte Carlo method and the tile-low-rank-matrix based Quasi-Monte Carlo method, respectively.

algorithm

Implementation of the classic Genz algorithm and a novel tile-low-rank algorithm for computing	relatively high-dimensional multivariate normal (MVN) and Student-t (MVT) probabilities.
References used for this package:
Foley, James, Andries van Dam, Steven Feiner, and John Hughes.
"Computer Graphics: Principle and Practice". Addison-Wesley
Publishing Company. Reading, Massachusetts (1987, ISBN:0-201-84840-6 1);
Genz, A., "Numerical computation of multivariate
normal probabilities," Journal of Computational and
Graphical Statistics, 1, 141-149 (1992) <doi:10.1080/10618600.1992.10477010>;
Cao, J., Genton, M. G., Keyes, D. E., & Turkiyyah, G. M. "Exploiting Low
Rank Covariance Structures for Computing High-Dimensional Normal and Student-
t Probabilities," Statistics and Computing, 31.1, 1-16 (2021)
<doi:10.1007/s11222-020-09978-y>;
Cao, J., Genton, M. G., Keyes, D. E., & Turkiyyah, G. M. "tlrmvnmvt:
Computing High-Dimensional Multivariate Normal and Student-t Probabilities
with Low-Rank Methods in R," Journal of Statistical Software, 101.4,
1-25 (2022) <doi:10.18637/jss.v101.i04>.

algorithm: Parameters for the Quasi-Monte Carlo sampling

Description

Usage

Arguments

Value