Maximum Likelihood Estimation for Probability Functions from Data Sets

A routine for parameter estimation for any probability density or mass function implemented in R via maximum likelihood (ML) given a data set. This routine is a wrapper function specifically developed for ML estimation. There are included optimization procedures such as 'nlminb' and 'optim' from base package, and 'DEoptim' Mullen (2011) . Standard errors are estimated with 'numDeriv' Gilbert (2011) <> or the option 'Hessian = TRUE' of 'optim' function.


Reference manual

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1.2.0 by Jaime Mosquera, 14 days ago

Browse source code at

Authors: Jaime Mosquera [aut, cre] , Freddy Hernandez [aut]

Documentation:   PDF Manual  

GPL-3 license

Imports Rdpack, knitr, rmarkdown

Depends on stats, DEoptim, boot, numDeriv, BBmisc

Suggests gamlss.dist

See at CRAN