scores {hetGP}

Score and RMSE function To asses the performance of the prediction, this function computes the root mean squared error and proper score function (also known as negative log-probability density).

Description

Score and RMSE function To asses the performance of the prediction, this function computes the root mean squared error and proper score function (also known as negative log-probability density).

Usage

scores(model, Xtest, Ztest, return.rmse = FALSE)

Arguments

model

homGP or hetGP model, including inverse matrices

Xtest

matrix of new design locations

Ztest

corresponding vector of observations, or alternatively, a matrix of size [nrow(Xtest) x number of replicates], a list of size nrow(Xtest) with a least one value per element

return.rmse

if TRUE, return the root mean squared error

References

T. Gneiting, and A. Raftery (2007). Strictly Proper Scoring Rules, Prediction, and Estimation, Journal of the American Statistical Association, 102(477), 359-378.