window: Trim the sequence of hyperparameter estimates within a DGP...

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

Trim the sequence of hyperparameter estimates within a DGP emulator

Description

This function trims the sequence of hyperparameter estimates within a DGP emulator generated during training.

Usage

window(object, start, end = NULL, thin = 1)

Arguments

object	an instance of the S3 class dgp.
start	the first iteration before which all iterations are trimmed from the sequence.
end	the last iteration after which all iterations are trimmed from the sequence. Set to NULL to keep all iterations after (including) start. Defaults to NULL.
thin	the interval between the start and end iterations to thin out the sequence. Defaults to 1.

Details

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

Value

An updated object with a trimmed sequence of hyperparameters.

Note

• This function is useful when a DGP emulator has been trained and one wants to trim the sequence of hyperparameters estimated and to use the trimmed sequence to generate point estimates of the DGP model parameters for prediction.

• The following slots:

  • loo and oos created by validate(); and

  • results created by predict() in object will be removed and not contained in the returned object.

Examples

## Not run: 

# See dgp() for an example.

## End(Not run)

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