pmvn {VeccTMVN} | R Documentation |
Compute multivariate normal (MVN) probabilities that have spatial covariance matrices using Vecchia approximation
pmvn(
lower,
upper,
mean,
locs = NULL,
covName = "matern15_isotropic",
covParms = c(1, 0.1, 0),
m = 30,
sigma = NULL,
reorder = 0,
NLevel1 = 12,
NLevel2 = 10000,
verbose = FALSE,
retlog = FALSE,
...
)
lower |
lower bound vector for TMVN |
upper |
upper bound vector for TMVN |
mean |
MVN mean |
locs |
location (feature) matrix n X d |
covName |
covariance function name from the 'GpGp' package |
covParms |
parameters for 'covName' |
m |
Vecchia conditioning set size |
sigma |
dense covariance matrix, not needed when 'locs' is not null |
reorder |
whether to reorder integration variables. '0' for no, '1' for FIC-based univariate ordering, '2' for Vecchia-based univariate ordering, and '3' for the reordering implemented in TruncatedNormal, which appeared faster than '2' |
NLevel1 |
first level Monte Carlo sample size |
NLevel2 |
second level Monte Carlo sample size |
verbose |
verbose or not |
retlog |
TRUE or FALSE for whether to return loglk or not |
... |
could be m_ord for conditioning set size for reordering |
estimated MVN probability and estimation error