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Strategies for fitting nonlinear ecological models in R, AD Model Builder, and BUGS
Article first published online: 22 APR 2013
DOI: 10.1111/2041-210X.12044
© 2013 The Authors. Methods in Ecology and Evolution © 2013 British Ecological Society
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How to Cite
Bolker, B. M., Gardner, B., Maunder, M., Berg, C. W., Brooks, M., Comita, L., Crone, E., Cubaynes, S., Davies, T., de Valpine, P., Ford, J., Gimenez, O., Kéry, M., Kim, E. J., Lennert-Cody, C., Magnusson, A., Martell, S., Nash, J., Nielsen, A., Regetz, J., Skaug, H., Zipkin, E. (2013), Strategies for fitting nonlinear ecological models in R, AD Model Builder, and BUGS. Methods in Ecology and Evolution, 4: 501–512. doi: 10.1111/2041-210X.12044
Publication History
- Issue published online: 7 JUN 2013
- Article first published online: 22 APR 2013
- Accepted manuscript online: 28 FEB 2013 08:35AM EST
- Manuscript Accepted: 19 FEB 2013
- Manuscript Received: 22 NOV 2012
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Keywords:
- JAGS ;
- optimization;
- parameter estimation;
- R ;
- AD Model Builder;
- WinBUGS
Summary
- Ecologists often use nonlinear fitting techniques to estimate the parameters of complex ecological models, with attendant frustration. This paper compares three open-source model fitting tools and discusses general strategies for defining and fitting models.
- R is convenient and (relatively) easy to learn, AD Model Builder is fast and robust but comes with a steep learning curve, while BUGS provides the greatest flexibility at the price of speed.
- Our model-fitting suggestions range from general cultural advice (where possible, use the tools and models that are most common in your subfield) to specific suggestions about how to change the mathematical description of models to make them more amenable to parameter estimation.
- A companion web site (https://groups.nceas.ucsb.edu/non-linear-modeling/projects) presents detailed examples of application of the three tools to a variety of typical ecological estimation problems; each example links both to a detailed project report and to full source code and data.