CGGPvalstats: Calculate stats for CGGP prediction on validation data

In CollinErickson/CGGP: Composite Grid Gaussian Processes

Calculate stats for CGGP prediction on validation data

Description

Calculate stats for CGGP prediction on validation data

Usage

CGGPvalstats(CGGP, Xval, Yval, bydim = TRUE, ...)

Arguments

CGGP	CGGP object
Xval	X validation matrix
Yval	Y validation data
bydim	If multiple outputs, should it be done separately by dimension?
...	Passed to valstats, such as which stats to calculate.

Value

data frame

Examples

SG <- CGGPcreate(d=3, batchsize=100)
f1 <- function(x){x[1]+x[2]^2}
y <- apply(SG$design, 1, f1)
SG <- CGGPfit(SG, y)
Xval <- matrix(runif(3*100), ncol=3)
Yval <- apply(Xval, 1, f1)
CGGPvalstats(CGGP=SG, Xval=Xval, Yval=Yval)

# Multiple outputs
SG <- CGGPcreate(d=3, batchsize=100)
f1 <- function(x){x[1]+x[2]^2}
f2 <- function(x){x[1]^1.3+.4*sin(6*x[2])+10}
y1 <- apply(SG$design, 1, f1)#+rnorm(1,0,.01)
y2 <- apply(SG$design, 1, f2)#+rnorm(1,0,.01)
y <- cbind(y1, y2)
SG <- CGGPfit(SG, Y=y)
Xval <- matrix(runif(3*100), ncol=3)
Yval <- cbind(apply(Xval, 1, f1),
              apply(Xval, 1, f2))
CGGPvalstats(SG, Xval, Yval)
CGGPvalstats(SG, Xval, Yval, bydim=FALSE)

CollinErickson/CGGP documentation built on Feb. 6, 2024, 2:24 a.m.