Description Usage Arguments Value Author(s) References See Also Examples
View source: R/lineqGPsamplers.R
Sampler for truncated multivariate normal distributions via RSM according to (Maatouk and Bay, 2017).
1 2 |
object |
an object with |
nsim |
an integer corresponding to the number of simulations. |
control |
extra parameters required for the MC/MCMC sampler. |
... |
further arguments passed to or from other methods. |
A matrix with the simulated samples. Samples are indexed by columns.
A. F. Lopez-Lopera.
Maatouk, H. and Bay, X. (2017), "Gaussian process emulators for computer experiments with inequality constraints". Mathematical Geosciences, 49(5):557-582. [link]
1 2 3 4 5 6 7 8 9 | n <- 100
x <- seq(0, 1, length = n)
Sigma <- kernCompute(x1 = x, type = "gaussian", par = c(1,0.2))
tmgPar <- list(mu = rep(0,n), Sigma = Sigma + 1e-9*diag(n), lb = rep(-1,n), ub = rep(1,n))
class(tmgPar) <- "RSM"
y <- tmvrnorm(tmgPar, nsim = 10)
matplot(x, y, type = 'l', ylim = c(-1,1),
main = "Constrained samples using RSM")
abline(h = c(-1,1), lty = 2)
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