Public domain ADMB project

Principal Investigators:

John R. Sibert, and Mark N. Maunder

AD Model Builder (ADMB) is a tool for developing integrated statistical models of complex systems. The principle advantages of the ADMB software suite over other approaches are rapid model development, numerical stability, computational speed, precision of model estimates, and the capacity to accommodate relatively large numbers of parameters and data points. The ADMB software has earned acceptance by researchers working on all aspects of resource management. Population models based on the ADMB software are used to monitor more than 150 different... more

Participants and Meetings

ActivityDatesFurther Information
Training Workshop9th—10th March 2009Participant List  
Working Group20th—23rd June 2011Participant List  

Participant Contact Information

Johnoel Anchetajohnoel@hawaii.eduUniversity of Hawaii, Mānoa
Carol A. Blanchetteblanchette@msi.ucsb.eduUniversity of California, Santa Barbara
Sylvain Bonhommeausylvain.bonhommeau@gmail.comUniversity of California, Santa Barbara
Greg A. Breedgbreed@ualberta.caUniversity of California, Santa Cruz
Jennifer E. Casellecaselle@lifesci.ucsb.eduUniversity of California, Santa Barbara
Frank Davenportdavenpor@geog.ucsb.eduUniversity of California, Santa Barbara
Trevor D. Daviestdavies@mathstat.dal.caDalhousie University
Kelly L. DeckerKelly.L.Decker@nasa.govNASA Ames Research Center
Stephanie E. Hamptonshampton@nsf.govUniversity of California, Santa Barbara
Carrie V. Kappelkappel@nceas.ucsb.eduUniversity of California, Santa Barbara
Brian P. Kinlankinlan@lifesci.ucsb.eduUniversity of California, Santa Barbara
Tin Klanjscektin@lifesci.ucsb.eduUniversity of California, Santa Barbara
Robert Leafrleap@vt.eduVirginia Polytechnic Institute and State University
Steven Y. Litvinlitvin@stanford.eduStanford University
Alexander Lowelowe@msi.ucsb.eduUniversity of California, Santa Barbara
Mark N. Maundermmaunder@iattc.orgInterAmerican Tropical Tuna Commission
Duncan N. Mengedm2972@columbia.eduUniversity of California, Santa Barbara
Erik B.
Anders Nielsenanders@nielsensweb.orgUniversity of Hawaii
Mary I. O'Connoroconnor@zoology.ubc.caUniversity of California, Santa Barbara
Laure Pecqueriepecquerie@lifesci.ucsb.eduUniversity of California, Santa Barbara
Christopher R. Perlecperle@stanford.eduStanford University
Christine Petersenpetersen@nceas.ucsb.eduUniversity of California, Santa Barbara
Jai Ranganathanranganathan@nceas.ucsb.eduUniversity of California, Santa Barbara
James Regetzregetz@gmail.comUniversity of California, Santa Barbara
Mark P. Schildhauerschild@nceas.ucsb.eduUniversity of California, Santa Barbara
Ulrich K. Steinerusteiner@stanford.eduStanford University
Crow Whitecwhite31@calpoly.eduUniversity of California, Santa Barbara
Arliss Winishiparliss@mathstat.dal.caDalhousie University
Teresa A'marteresa.amar@noaa.govNational Oceanic and Atmospheric Administration (NOAA)
Mollie Brooksmbrooks@ufl.eduMcMaster University
David A. Fournierdavef@otter-rsch.comOtter Research Ltd.
Chris Grandinchris.grandin@dfo-mpo.gc.caFisheries and Oceans Canada
Brian Lintonbrian.linton@noaa.govNOAA, National Marine Fisheries Service (NMFS)
Weihai Liuliuweih@msu.eduMichigan State University
Arni Magnussonarnima@hafro.isMarine Research Institute
Steve J.D. Martells.martell@fisheries.ubc.caUniversity of British Columbia
Derek Seipledseiple84@gmail.comUniversity of Hawaii
John R. Sibertsibert@hawaii.eduUniversity of Hawaii, Mānoa
Tim Sippeltsippel@gmail.comUniversity of Hawaii, Mānoa
Hans J. Skaughans.skaug@math.uib.noUniversity of Bergen
Casper Willestofte Bergcbe@aqua.dtu.dkTechnical University of Denmark

Products: Publications, Reports, Datasets, Presentations, Visualizations

TypeProduct of NCEAS Research
Journal Article Fournier, David A.; Skaug, Hans J.; Ancheta, Johnoel; Ianelli, James; Magnusson, Arni; Maunder, Mark N.; Nielsen, Anders; Sibert, John R. 2012. AD Model Builder: Using automatic differentiation for statistical inference of highly parameterized complex nonlinear models. Optimization Methods & Software. Vol: 27(2). Pages 233-249. (Online version)
"Public domain ADMB project" is project ID: 12204