Description Usage Arguments Details Value Author(s) See Also Examples
The function updates the current covariance models
stored in 'qsd
'.
1 2 |
qsd |
object of class |
nextData |
object of class |
fit |
logical, if |
cl |
cluster object, |
controls |
list of control parameters passed to |
verbose |
logical, whether to print intermediate information |
The function updates both, the covariance models for kriging the statistics, and, if applicable,
the ones for kriging the variance matrix of statistics based on the new data nextData
. In practice, the user hardly
needs to call this function except for empirical studies of how additional sample points might influence the overall predictive
quality of the quasi-score and/or criterion function approximations.
If 'fit
' equals TRUE
, then the function re-estimates the covariance parameters for each statistic separately
each time a total of 'qsd$nfit
' new sample points have been added. Thus, we can choose whether to fit the updated
covariance models (by the REML estimation) each time, e.g. during the estimation by qle
if 'qsd$nfit
'=1, or after
each 2nd, 3rd, and so on newly added point in order to limit the computational overhead.
Object of class QLmodel
as a list of updated covariance models
M. Baaske
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | data(normal)
# old design
X <- as.matrix(qsd$qldata[c(1,2)])
# augment design with two additional points
Xnew <- multiDimLHS(N=2,qsd$lower,qsd$upper,X=X,
method="augmentLHS",type="matrix")
# new simulations
Xsim <- simQLdata(sim=qsd$simfn,nsim=10,X=Xnew)
# prepare data
Xdata <- setQLdata(Xsim,Xnew)
# do not re-estimate covariance parameters
qsd2 <- updateCovModels(qsd,Xdata,fit=FALSE)
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