1. Nonlinear, parametric curve-fitting provides a framework for understanding diverse ecological and evolutionary trends (e.g. growth patterns and seasonal cycles). Currently, parametric curve-fitting requires a priori assumptions of curve trajectories, restricting their use for exploratory analyses. Furthermore, use of analytical techniques [nonlinear least-squares (NLS) and nonlinear mixed-effects models] for complex parametric curves requires efficient choice of starting parameters. 2. We illustrate the new R package FlexParamCurve that automates curve selection and provides tools to analyse nonmonotonic curve data in NLS and nonlinear mixed-effects models. Examples include empirical and simulated data sets for the growth of seabird chicks. 3. By automating curve selection and parameterization during curve-fitting, FlexParamCurve extends current possibilities for parametric analysis in ecological and evolutionary studies. Video. Video © 2012 The Authors. Methods in Ecology and Evolution © 2012 British Ecological Society.
CITATION STYLE
Oswald, S. A., Nisbet, I. C. T., Chiaradia, A., & Arnold, J. M. (2012). FlexParamCurve: R package for flexible fitting of nonlinear parametric curves. Methods in Ecology and Evolution, 3(6), 1073–1077. https://doi.org/10.1111/j.2041-210X.2012.00231.x
Mendeley helps you to discover research relevant for your work.