NCEAS Project 12602

Evaluating and improving open source software for nonlinear statistical modeling in ecology

  • Mark N. Maunder
  • Benjamin Bolker
  • Beth Gardner

ActivityDatesFurther Information
Working Group10th—14th January 2011Participant List  
Working Group18th—22nd July 2011Participant List  

Abstract
Increasingly, non‐linear and complex models are applied as a tool for improving understanding of ecological systems. These statistical models are often used to test hypotheses and make inferences about ecological theories and management decisions based on available data. This explosion in the application of such models is due to rapid and current development of methodology to carryout statistical inference of complex nonlinear models and improvements in computer power (faster and multiple processors). While there are many tools available for statistical inference that differ in their effectiveness for specific applications, no formal comparisons have been conducted between various software packages. It is therefore important to identify which tools are most appropriate for given applications and to demonstrate how such tools can be used most effectively. We evaluate three open source software packages commonly used to carry out statistical inference of complex nonlinear models: OpenBUGS, AD Model Builder, and R. To test the strengths and weaknesses of each package, we will bring together experts in all three software packages and apply a common set of ecological models. Working directly with NCEAS informatics staff, we will produce a web‐based guide regarding the utility of each package for particular applications that includes annotated model code for each package, the data sets used in the applications, and peer‐reviewed articles. We will also identify how the different packages can be modified to improve their applicability to an array of complex nonlinear models that are essential for advancing ecological research. As statistical models are becoming increasingly more complex and ecologists are faced with a myriad of software options, the results of this project will provide support for ecologists and analysts across a broad spectrum of specialties.

TypeProducts of NCEAS Research
Journal Article Bolker, Benjamin; Gardner, Beth; Maunder, Mark N.; Berg, Casper W.; Brooks, Mollie; Comita, Liza S.; Crone, Elizabeth E.; Cubaynes, Sarah; Davies, Trevor D.; de Valpine, Perry; Ford, Jessica; Gimenez, Olivier; Kéry, Marc; Kim, Eunjung; Lennert-Cody, Cleridy; Magnusson, Arni; Martell, Steve J.D.; Nash, John C.; Nielsen, Anders; Regetz, Jim; Skaug, Hans J.; Zipkin, Elise. 2013. Strategies for fitting nonlinear ecological models in R, AD Model Builder, and BUGS. Methods in Ecology and Evolution. Vol: 4. Pages 501-512. (Online version)
Journal Article Nash, John C.; Varadhan, Ravi. 2011. Unifying optimization algorithms to aid software system users: Optimx for R. Journal of Statistical Software. Vol: 43(9). Pages 1-9.