Infusion (version 1.1.0)

MSL: Maximum likelihood from an inferred likelihood surface

Description

This computes the maximum of an object of class SLik representing an inferred (summary) likelihood surface

Usage

MSL(object, CIs = TRUE, level = 0.95, verbose = interactive(),
    eval_RMSEs = inherits(object,"SLik"), ...)

Arguments

object

an object of class SLik as produced by infer_surface.logLs

CIs

If TRUE, construct one-dimensional confidence intervals for all parameters.

level

Intended coverage probability of the confidence intervals.

verbose

Whether to display some information about progress and results.

eval_RMSEs

Logical: whether to evaluate prediction uncertainty for likelihoods/ likelihood ratios/ parameters. By default TRUE for SLik objects, and best kept so, as it is necessary for the automated iterative method. May be FALSE for other classes of objects.

…

Further arguments passed from or to other methods.

Value

The object is returned invisibly, with added members

MSL

, itself with members MSLE and maxlogL that match the par and value returned by an optim call.

RMSEs

root mean square errors of the log-likelihood at its inferred maximum and of the log-likelihood ratios at the CI bounds.

par_RMSEs

root mean square errors of the CI bounds

Details

RMSEs are computed using approximate formulas for prediction (co-)variances in linear mixed midels (see Details in predict). par_RMSEs are computed from RMSEs and from the numerical gradient of profile log-likelihood at each CI bound.

Examples

# NOT RUN {
## see main documentation page for the package
# }