pmvn {VeccTMVN} | R Documentation |
Compute multivariate normal (MVN) probabilities that have spatial covariance matrices using Vecchia approximation
Description
Compute multivariate normal (MVN) probabilities that have spatial covariance matrices using Vecchia approximation
Usage
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,
...
)
Arguments
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, and '2' for Vecchia-based univariate ordering |
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 |
Value
estimated MVN probability and estimation error
[Package VeccTMVN version 1.0.0 Index]