Calculate negative predicted log-likelihoodSource:
This function computes the negative predicted log-likelihood from a DGP emulator with a likelihood layer.
an instance of the
dgpclass and it should be produced by
dgp()with one of the following two settings:
a matrix where each row is an input testing data point and each column is an input dimension.
a matrix with only one column where each row is a scalar-valued testing output data point.
object is returned with an additional slot named
NLL that contains two elements.
The first one, named
meanNLL, is a scalar that gives the average negative predicted log-likelihood
across all testing data points. The second one, named
allNLL, is a vector that gives the negative predicted
log-likelihood for each testing data point.
See further examples and tutorials at https://mingdeyu.github.io/dgpsi-R/.
Any R vector detected in
y will be treated as a column vector and automatically converted into a single-column
R matrix. Thus, if
x is a single testing data point with multiple dimensions, it must be given as a matrix.