Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
84157 | Computers and Electronics in Agriculture | 2015 | 4 Pages |
•A tool for fitting growth functions to be used in forestry was developed.•Twelve selected growth models both classical and new are implemented.•The tool employs robust and efficient algorithms proposed by MATLAB.•The tools allows evaluation of models, prediction and graphical outputs.•Models can be adjusted for individual data points.
We present a tool (KORFit) for fitting growth functions to empirical data, primarily for forest management applications, but also can be applied in other biological fields. KORFit fits data using 12 growth functions. Increment curves are produced, and growth magnitude and increment values can be predicted for a given age. KORFit implements an efficient and robust algorithm of Levenberg–Marquardt non-linear least squares fitting method utilizing MATLAB libraries. Criteria for evaluating goodness of fit (e.g. Akaike information criterion, Bayesian information criterion, leave-one-out cross-validation) are implemented. Individualized curves for individual data point can be modeled.