MSL | R Documentation |
This computes the maximum of an object of class SLik
representing an inferred (summary) likelihood surface
MSL(object, CIs = prod(dim(object$logLs)) < 12000L, level = 0.95,
verbose = interactive(),
RMSE_n=Infusion.getOption("RMSE_nsim"),
eval_RMSEs=(RMSE_n>1L) * prod(dim(object$logLs))<12000L,
cluster_args=list(), nb_cores=NULL,
init=NULL, prior_logL=NULL)
object |
an object of class |
CIs |
If |
level |
Intended coverage probability of the confidence intervals. |
verbose |
Whether to display some information about progress and results. |
RMSE_n |
Integer: number of simulation replicates for evaluation of prediction uncertainty for likelihoods/ likelihood ratios/ parameters. The default value (10) provides quick but inaccurate estimates. |
eval_RMSEs |
Logical: whether to evaluate prediction uncertainty for likelihoods/ likelihood ratios/ parameters. |
cluster_args |
A list of arguments, passed to |
nb_cores |
Integer: shortcut for specifying |
init |
Initial value for the optimiser. Better ignored. |
prior_logL |
(effective only for up-to-date workflow using gaussian mixture modelling of a joint distribution of parameters and statistics) a function that returns a vector of prior log-likelihood values, which is then added to the likelihood deduced from the summary likelihood analysis. The function's single argument must handle a matrix similar to the |
If Kriging has been used to construct the likelihood surface, RMSEs
are computed using approximate formulas for prediction (co-)variances in linear mixed midels (see Details in predict
). Otherwise, a more computer-intensive bootstrap method is used.
par_RMSEs
are computed from RMSEs
and from the numerical gradient of profile log-likelihood at each CI bound. Only RMSEs
, not par_RMSEs
, are compared to precision
.
The object
is returned invisibly, with the following (possibly) added members, each of which being (as from version 1.5.0) an environment:
MSL
containing variables MSLE
and maxlogL
that match the par
and value
returned by an optim
call. Also contains the hessian
of summary likelihood at its maximum.
CIobject
The return value of calling allCIs
, converted to an environment.
RMSEs
containing, as variable RMSEs
, the root mean square errors of the log-likelihood at its inferred maximum and of the log-likelihood ratios at the CI bounds.
par_RMSEs
containing, as variable par_RMSEs
, root mean square errors of the CI bounds.
To ensure backward-compatibility of code to possible future changes in the structure of the objects, the extractor function get_from
should be used to extract the RMSEs
and par_RMSEs
variables from their respective environments, and more generally to extract any element from the objects.
## see main documentation page for the package
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