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 = FALSE,
reset = FALSE,
verb = TRUE,
N = NULL,
cores = 1,
ess_burn = 10,
B = NULL,
...
)
# S3 method for class '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 thegp
class,Y
is a matrix with only one column and each row being an output data point.If
object
is an instance of thedgp
class,Y
is a matrix with its rows being output data points and columns being output dimensions. Whenlikelihood
(see below) is notNULL
,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 toFALSE
.- 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 toFALSE
.- 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 thedgp
class. If set toNULL
, the number of iterations is set to100
if the DGP emulator was constructed without the Vecchia approximation, and is set to50
if Vecchia approximation was used. Defaults toNULL
.- 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)
ifvecchia = FALSE
andmax physical cores available %/% 2
ifvecchia = 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 to1
.- 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 thedgp
class. Defaults to10
.- B
the number of imputations for predictions from the updated emulator
object
if it is an instance of thedgp
class. This overrides the number of imputations set inobject
. Set toNULL
to use the same number of imputations set inobject
. Defaults toNULL
.
Details
See further examples and tutorials at https://mingdeyu.github.io/dgpsi-R/.
Note
The following slots:
loo
andoos
created byvalidate()
;results
created bypredict()
; anddesign
created bydesign()
in
object
will be removed and not contained in the returned object.