basisCompute.lineqGP: Hat Basis Functions for "lineqGP" Models
Description
Evaluate the hat basis functions for "lineqGP" models.
Usage
basisCompute.lineqGP(x, u, d = 1)
Arguments
x
a vector (or matrix) with the input data.
u
a vector (or matrix) with the locations of the knots.
d
a number corresponding to the dimension of the input space.
Value
A matrix with the hat basis functions. The basis functions are indexed by rows.
Comments
This function was tested mainly for 1D or 2D input spaces. It could change
in future versions for higher dimensions.
References
Lopez-Lopera, A. F., Bachoc, F., Durrande, N., and Roustant, O. (2017),
"Finite-dimensional Gaussian approximation with linear inequality constraints".
ArXiv e-prints[link]
Maatouk, H. and Bay, X. (2017),
"Gaussian process emulators for computer experiments with inequality constraints".
Mathematical Geosciences,
49(5): 557-582.
[link]
# NOT RUN {x <- seq(0, 1, 1e-3)
m <- 5
u <- seq(0, 1, 1/(m-1))
Phi <- basisCompute.lineqGP(x, u, d = 1)
matplot(Phi, type = "l", lty = 2, main = "Hat basis functions with m = 5")
# }