dgpsi (version 2.4.0)

continue: Continue the training of a DGP emulator

Description

This function implements additional training iterations for a DGP emulator.

Usage

continue(
  object,
  N = 500,
  cores = 1,
  ess_burn = 10,
  verb = TRUE,
  burnin = NULL,
  B = NULL
)

Value

An updated object.

Arguments

object

an instance of the dgp class.

N

additional number of iterations for the DGP emulator training. Defaults to 500.

cores

the number of cores/workers to be used to optimize GP components (in the same layer) at each M-step of the training. 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 of the training. Defaults to 10.

verb

a bool indicating if the progress bar will be printed during the training:

1. FALSE: the training progress bar will not be displayed.

2. TRUE: the training progress bar will be displayed.

Defaults to TRUE.

burnin

the number of training iterations to be discarded for point estimates calculation. Must be smaller than the overall training iterations so-far implemented. If this is not specified, only the last 25% of iterations are used. This overrides the value of burnin set in dgp(). Defaults to NULL.

B

the number of imputations to produce the predictions. Increase the value to account for more imputation uncertainties. This overrides the value of B set in dgp() if B is not NULL. Defaults to NULL.

Details

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

Examples

if (FALSE) {

# See dgp() for an example.
}