Update a GP or DGP emulator — update • dgpsi

This function updates the training input and output of a GP or DGP emulator with an option to refit the emulator.

Usage

update(object, X, Y, refit, reset, verb, ...)

# S3 method for dgp
update(
  object,
  X,
  Y,
  refit = FALSE,
  reset = FALSE,
  verb = TRUE,
  N = 100,
  cores = 1,
  ess_burn = 10,
  B = NULL,
  ...
)

# S3 method for gp
update(object, X, Y, refit = FALSE, reset = FALSE, verb = TRUE, ...)

Arguments

object

can be one of the following:

the S3 class gp.
the S3 class dgp.

X

the new input data which is a matrix where each row is an input training data point and each column is an input dimension.

Y

the new output data:

If object is an instance of the gp class, Y is a matrix with only one column and each row being an output data point.
If object is an instance of the dgp class, Y is a matrix with its rows being output data points and columns being output dimensions. When likelihood (see below) is not NULL, Y must be a matrix with only one column.

refit

a bool indicating whether to re-fit the emulator object after the training input and output are updated. Defaults to FALSE.

reset

a bool indicating whether to reset hyperparameters of the emulator object to their initial values when the emulator was constructed, after the training input and output are updated. Defaults to FALSE.

verb

a bool indicating if the trace information will be printed during the function execution. Defaults to TRUE.

...

N/A.

N

number of training iterations used to re-fit the emulator object if it is an instance of the dgp class. Defaults to 100.

cores

the number of cores/workers to be used to re-fit GP components (in the same layer) at each M-step during the re-fitting. If set to NULL, the number of cores is set to (max physical cores available - 1). Only use multiple cores when there is a large number of GP components in different layers and optimization of GP components is computationally expensive. Defaults to 1.

ess_burn

number of burnin steps for the ESS-within-Gibbs at each I-step in training the emulator object if it is an instance of the dgp class. Defaults to 10.

B

the number of imputations for predictions from the updated emulator object if it is an instance of the dgp class. This overrides the number of imputations set in object. Set to NULL to use the same number of imputations set in object. Defaults to NULL.

Value

An updated object.

Details

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

Note

The following slots:
- loo and oos created by validate();
- results created by predict(); and
- design created by design()
in object will be removed and not contained in the returned object.
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 data point with multiple dimensions, it must be given as a matrix.

Examples

if (FALSE) {

# See alm(), mice(), pei(), or vigf() for an example.
}