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Open AccessComputer ScienceMathematics

AD Model Builder: using automatic differentiation for statistical inference of highly parameterized complex nonlinear models

D. Fournier, H. Skaug, John Ancheta, J. Ianelli, A. Magnusson, M. Maunder, Anders Nielsen, J. Sibert

2012.3.7OPTIMIZATION METHODS & SOFTWARE

DOI: 10.1080/10556788.2011.597854

tlooto Summary

The basic components and the underlying philosophy of ADMB are described, with an emphasis on functionality found in no other statistical software, and the main advantages are flexibility, speed, precision, stability and built-in methods to quantify uncertainty.

Abstract

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Citation format

FOURNIER, D., et al. AD model builder: Using automatic differentiation for statistical inference of highly parameterized complex nonlinear models. OPTIMIZATION METHODS & SOFTWARE, 2012, 27: 233–249.