CGGP_internal_calcpw: Calculate predictive weights for CGGP

In CGGP: Composite Grid Gaussian Processes

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)

Arguments

CGGP	CGGP object
y	Measured values for CGGP$design
theta	Correlation parameters
return_lS	Should lS be returned?

Value

Vector with predictive weights

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)

CGGP documentation built on May 8, 2021, 5:06 p.m.