Regression error for Gaussian process regression model

`L = loss(gprMdl,Xnew,Ynew)`

L = loss(gprMdl,Xnew,Ynew,Name,Value)

returns
the mean squared error for the Gaussian process regression (GPR) model `L`

= loss(`gprMdl`

,`Xnew`

,`Ynew`

)`gpr`

,
using the predictors in `Xnew`

and observed response
in `Ynew`

.

returns
the mean squared error for the GPR model, `L`

= loss(`gprMdl`

,`Xnew`

,`Ynew`

,`Name,Value`

)`gpr`

,
with additional options specified by one or more `Name,Value`

pair
arguments. For example, you can specify a custom loss function or
the observation weights.

You can use `resubLoss`

to compute the regression error
for the trained GPR model at the observations in the training data.

`CompactRegressionGP`

| `RegressionGP`

| `compact`

| `fitrgp`

| `predict`

| `resubLoss`