nllik {dgpsi}

Calculate negative predicted log-likelihood

Description

This function computes the negative predicted log-likelihood from a DGP emulator with a likelihood layer.

Usage

nllik(object, x, y)

Arguments

object

an instance of the dgp class and it should be produced by dgp() with one of the following two settings:

1. if struc = NULL, likelihood is not NULL;

2. if a customized structure is provided to struc, the final layer must be likelihood layer containing only one likelihood node produced by Poisson(), Hetero(), or NegBin().

x

a matrix where each row is an input testing data point and each column is an input dimension.

y

a matrix with only one column where each row is a scalar-valued testing output data point.

Details

See further examples and tutorials at https://mingdeyu.github.io/dgpsi-R/.

Value

An updated 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.

Note

Any R vector detected in x and 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.

Examples

## Not run: 

# Check https://mingdeyu.github.io/dgpsi-R/ for examples
# on how to compute the negative predicted log-likelihood
# using nllik().

## End(Not run)