Description Usage Arguments Value See Also Examples
Calculate the BIC using the effective degrees of freedom of the kernel, rather than the number of free parameters
1 | bayesian.information.criterion.EDoF(gp.obj, ...)
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gp.obj |
A trained gaussianProcess object |
The BIC value for the input GP object.
model.search
and gaussianProcess
1 2 3 4 5 6 | x <- rnorm(50)
y <- sin(1/(x^2 + 0.15))
mt <- create.model.tree.builtin()
mt <- insert.kernel.instance(mt, 1, "SE", NULL, hyper.params=c(l=1))
gp <- create.gaussian.process(x, y, mt)
gp$fit.hyperparams(NA)
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