Research Institute for Industrial Crops |
Tools
for Agrometeorology and Agricultural Modelling |
Agronomy Group |
IRENE
The program IRENE (Integrated Resources for Evaluating Numerical Estimates) is a data analysis tool designed to provide easy access to model evaluation techniques. The literature gives neither a standard theory on model evaluation, nor a standard 'box of tools', but a plethora of philosophical theories, statistical techniques, and software practices. The emphasis is here given on statistical techniques, to be applied to comparing estimates (Ei) against measurements (Mi). Mostly, non-replicated estimates are compared against the non-replicated measurements. The program also allows comparing individual estimates against replicated measurements (or vice versa) and replicated estimates against replicated measurements. The program provides extensive statistical capabilities with tools for a variety of needs. Ready-to-use procedures handle a wide range of statistical indices and test statistics. Basic statistics allow a preliminary data quality check. The evaluation of model performance is essentially based on the difference Ei-Mi, designated as model residual (or, simply, residual), or on the correlation-regression Ei vs. Mi (or vice versa). In addition, model evaluation by probability distributions (i.e., probability of exceedence), residual analysis (i.e., pattern indices), or fuzzy-based aggregation statistics is allowed. Graphics are included in most analytical tasks, and the user can request many types of graphs directly. The results are displayed in separate spreadsheets and can be exported in MS Excel workbooks.
| Download
the software |
Download
the manual |
| |
|
|
visitor no.
![]() ![]() ![]() ![]()
|
References
Fila G., Bellocchi G., Acutis M., Donatelli M., 2001. IRENE: a software to test model performance. Proc. 2nd Int. Symp. Modelling Cropping Systems, 16-18 July, Florence, Italy, 215-216. (poster)
Fila G., Bellocchi G., Acutis M., Donatelli M., 2003. IRENE: a software to evaluate model performance. Eur. J. Agron., 18, 369-372. (abstract) (paper)