bbmle

Log likelihoods and model selection for mle2 objects

Compute table of information criteria and auxiliary info

convert profile to data frame

Convert calls to character

Normal distribution with profiled-out standard deviation

extract model names

Class "mle2". Result of Maximum Likelihood Estimation.

Maximum Likelihood Estimation

Options for maximum likelihood estimation

drop unneeded names from list elements

get and set parameter names

generate population prediction sample from parameters

Predicted values from an mle2 fit

Likelihood profiles

Methods for likelihood profiles

reconstruct the structure of a list

Abstract definitions of distributions

Calculate likelihood "slices"

likelihood-surface slices

Wrap strings at white space and + symbols

Class "summary.mle2", summary of "mle2" objects