gp.realize: Draw an unconditional GP realization.
In cmce: Computer Model Calibration for Deterministic and Stochastic Simulators

Description Usage Arguments Value See Also Examples

The list l.v is created by makedistlist() from a n x p design matrix on which to generate the unconditional GP realization. The correlation parameters take on values in (0,1) and use the Gaussian correlation model, calculated as rho^d(xi,xj)^2. This helper function is used to create the demonstration data used in the example for calibrate().

1	gp.realize(l.v,mu,lambda,rhos,lambdaf=Inf,eps=1e-10,from="")

`l.v`	A list of difference matrices for the design as calculated by `makedistlist()`
`mu`	An `n x 1` mean vector for the realization
`lambda`	A scalar quantity for the marginal precision of the drawn realization
`rhos`	A `p x 1` vector of correlation parameters
`lambdaf`	A scalar quantity denoting the precision of the error (i.i.d.) component of the realization
`eps`	A fudge factor to help with inverting large correlation matrices
`from`	Internal use only

An n x 1 vector of the GP realization calculated over the finite locations of the original design matrix.

getranges scaledesign makedistlist

library(cmce)

design=matrix(runif(10,1,5),ncol=2,nrow=5)
r=getranges(design)
design=scaledesign(design,r)
l.v=makedistlist(design)
rho=c(0.2,0.01)
muv=rep(0,nrow(design))
lambdav=1
surface=gp.realize(l.v,muv,lambdav,rho)