bbmle: Tools for General Maximum Likelihood Estimation

Methods and functions for fitting maximum likelihood models in R.

Depends: R (≥ 3.0.0), stats4
Imports: stats, numDeriv, lattice, MASS, methods, bdsmatrix, Matrix, mvtnorm
Suggests: emdbook, rms, ggplot2, RUnit, MuMIn, AICcmodavg, Hmisc, optimx (≥ 2013.8.6), knitr, testthat
Published: 2020-02-03
Author: Ben Bolker [aut, cre], R Development Core Team [aut], Iago Giné-Vázquez [ctb]
Maintainer: Ben Bolker <bolker at>
License: GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation: no
Materials: NEWS
CRAN checks: bbmle results


Reference manual: bbmle.pdf
Vignettes: Examples for enhanced mle code
quasi: notes on quasi-likelihood/qAIC analysis inR
Package source: bbmle_1.0.23.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: bbmle_1.0.23.1.tgz, r-oldrel: bbmle_1.0.23.1.tgz
Old sources: bbmle archive

Reverse dependencies:

Reverse depends: frair, sads
Reverse imports: bivgeom, DEsingle, econet, emdbook, fitODBOD, fusionclust, Luminescence, M3Drop, metaplus, mistr, RJafroc, robmixglm, rstpm2, scRecover, ss3sim, WLinfer
Reverse suggests: broom, copula, epimdr, glmmTMB, insight, nlraa, parameters, primer, R2admb, SEERaBomb


Please use the canonical form to link to this page.