The function estimates the (hyper)parameters of a list of covariance models '
the Restricted Maximum Likelihood (REML) estimation method.
object either of class
matrix of sample points (design points)
data frame of simulated sample means of statistics
first column corresponds to the first model in the list '
list of control parameters, see
The function fits a list of covariance models using the REML method. In order to avoid singularities
of the so-called trend matrices make sure to use at least the minimum required number of sample points given by
Xs' which depends on trend order, see
setCovModel. THe use is given an advice if the trend order does
not match the required number of (initial) design points.
An object of class
reml which consists of a list of named lists
(of elements '
model' and '
convergence') each storing a fitted covariance model
together with optimization results from a call to
nloptr as an attribute
verbose=TRUE. The default method for estimation is
uses random starting points and thus produces different results if it is run more than onces. If the results strongly vary,
then the corresponding REML function might have many local minima which precludes the use of this default algorithm and another
one, e.g. '
nloptr.print.options), might lead to better results.
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