update: Update a GP or DGP emulator

In dgpsi: Interface to 'dgpsi' for Deep and Linked Gaussian Process Emulations

Update a GP or DGP emulator

Description

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 class 'dgp'
update(
  object,
  X,
  Y,
  refit = TRUE,
  reset = FALSE,
  verb = TRUE,
  N = NULL,
  cores = 1,
  ess_burn = 10,
  B = NULL,
  ...
)

## S3 method for class 'gp'
update(object, X, Y, refit = TRUE, 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 represents 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 TRUE.
reset	a bool indicating whether to reset hyperparameters of the emulator object to the initial values first obtained when the emulator was constructed. Use if it is suspected that a local mode for the hyperparameters has been reached through successive updates. Defaults to FALSE.
verb	a bool indicating if 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. If set to NULL, the number of iterations is set to 100 if the DGP emulator was constructed without the Vecchia approximation, and is set to 50 if Vecchia approximation was used. Defaults to NULL.
cores	the number of processes 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 processes is set to ⁠(max physical cores available - 1)⁠ if vecchia = FALSE and ⁠max physical cores available %/% 2⁠ if vecchia = TRUE. Only use multiple processes 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 sampler at each I-step of the training of 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.

Details

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

Value

An updated object.

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.

Examples

## Not run: 

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

## End(Not run)

dgpsi documentation built on April 3, 2025, 9:26 p.m.