MSL | R Documentation |

This computes the maximum of an object of class `SLik`

representing an inferred (summary) likelihood surface

MSL(object, CIs = TRUE, level = 0.95, verbose = interactive(), eval_RMSEs = TRUE, cluster_args=list(),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. |

`eval_RMSEs` |
Logical: whether to evaluate prediction uncertainty for likelihoods/ likelihood ratios/ parameters. |

`cluster_args` |
A list of arguments, passed to |

`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 |

`...` |
Further arguments passed from or to other methods. |

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 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 contain the`hessian`

of summary likelihood at its maximum.`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

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.