This method provides a diagnostic plot for the validation of a funGp Gaussian process model. It displays a calibration plot based on the leave-one-out predictions of the output at the points used to train the model.

# S4 method for fgpm
plotLOO(model, ...)



an object of class fgpm corresponding to the funGp model to validate.


additional arguments affecting the plot. The following typical graphics parameters are valid entries: xlim, ylim, xlab, ylab, main.



See also

* fgpm for the construction of funGp models;

* plotPreds for prediction plots;

* plotSims for simulation plots.


# generating input and output data for training
set.seed(100) <- 25
sIn <- expand.grid(x1 = seq(0,1,length = sqrt(, x2 = seq(0,1,length = sqrt(
fIn <- list(f1 = matrix(runif(*10), ncol = 10), f2 = matrix(runif(*22), ncol = 22))
sOut <- fgp_BB3(sIn, fIn,

# building the model
m1 <- fgpm(sIn = sIn, fIn = fIn, sOut = sOut)

# plotting the model