CGGP (version 1.0.4)

CGGP_internal_calcpw: Calculate predictive weights for CGGP

Description

Predictive weights are Sigma^(-1)*y in standard GP. This calculation is much faster since we don't need to solve the full system of equations.

Usage

CGGP_internal_calcpw(CGGP, y, theta, return_lS = FALSE)

Value

Vector with predictive weights

Arguments

CGGP

CGGP object

y

Measured values for CGGP$design

theta

Correlation parameters

return_lS

Should lS be returned?

Examples

cggp <- CGGPcreate(d=3, batchsize=100)
y <- apply(cggp$design, 1, function(x){x[1]+x[2]^2+rnorm(1,0,.01)})
CGGP_internal_calcpw(CGGP=cggp, y=y, theta=cggp$thetaMAP)