ADMB Project

ADMB-12.0
Released December 21, 2017

Overview

The ADMB (Automatic Differentiation Model Builder) software suite is an environment for nonlinear statistical modeling enabling rapid model development, numerical stability, fast and efficient computation, and high accuracy parameter estimates. AD Model Builder is a high level language built around the AUTODIF Library, a C++ language extension which transparently implements reverse mode automatic differentiation. A closely related software package, ADMB-RE, implements random effects in nonlinear models.

ADMB is an open source project. Read the AD Model Builder LICENSE.

Donations

ADMB is freely available for download. If you would like to contribute or donate funds, please contact users@admb-project.org.

ADMB Citation

Fournier, D.A., Skaug, H.J., Ancheta, J., Ianelli, J., Magnusson, A., Maunder, M.N., Nielsen, A., and Sibert, J. 2012. AD Model Builder: using automatic differentiation for statistical inference of highly parameterized complex nonlinear models. Optim. Methods Softw. 27:233-249.

The abstract and publication can be freely downloaded from the publisher.

Documentation

Read release notes for changes and features in CHANGES.

Read the installation procedures in INSTALL for Unix and Windows computers.

User manuals for AD Model Builder, the AUTODIF library and the ADMB-RE nonlinear random effects module are in the ADMB downloads.

Additional documentation is also available on the ADMB website.

Help and Support

For help and support, email users@admb-project.org.

Mailing list archives

Users is the general mailing list.
Developers is core team mailing list.

Contributors

The ADMB software was originally developed by David Fournier of Otter Research Ltd.

Thanks to the following who have contributed to the ADMB Project by providing fixes and/or suggestions:

David Fournier
John Sibert
Bill Clark
Hans Skaug
Mark Maunder
Anders Nielsen
Arni Magnusson
Ian Taylor
Chris Grandin
Derek Seiple
Jan Jaap Poos
Gareth Williams
Weihai Liu
Barak A. Pearlmutter
Jon Schnute
Jiashen Tang
William Stockhausen - NOAA
Allan Hicks
Johnoel Ancheta