1. Models published in the literature | 2. Simulating phenology | 2.1. Temperature time series | 2.2. Model selection and computation | 2.2.1. Simulation using a single model | 2.2.2. Simulation using different models | 2.3. Simulation results and comparison | Legal information

1. Using inpdfr from command line | 1.1 Obtaining the word-occurrence data.frame from a set of documents | 1.1.1. Extracting text from PDF | 1.1.2. Excluding stop words | 1.1.3. Truncation of the number of words | 1.1.4. Merging data.frames | 1.1.5. Quick function | 1.2. Computing a set of analysis from the word-occurrence data.frame | 1.2.1. Simple manipulations of the word occurrence data.frame | 1.2.2. Word cloud | 1.2.3. Summary statistics | 1.2.4. Word frequency | 1.2.5. Correspondance analysis | 1.2.6. Cluster analysis | 1.2.7. K-means cluster analysis | 1.2.8. Metacommunity analysis with entropart | 1.2.9. Metacommunity analysis with metacom | 1.2.10. Quick function | 2. Using inpdfr from the Graphical User Interface (GUI) | 3. Going further

Organizing the dataset | Finding models in the literature | Fitting models to empirical datasets | Models comparison | Forecasting phenologies from empirical temperature

Recordatorios sobre biología de insectos | Datos del laboratorio | Seleccionar un modelo y ajustarlo | El modelo lineal | Los modelos no lineales | Construir modelos fenológicos | Límites | Conclusión

Nonlinear models | Datasets | Fitting the six models to the eight empirical datasets | [1] Briere-1 model | [2] Briere-2 model | [3] Lactin model | [4] Performance-2 Model | [5] Beta model | [6] Ratkowsky model | Organizing models' results | [1] RSS | [2] R squared | [3] R squared adjusted | [4] RMSE | [5] AIC corrected | [6] AIC | Visualization | Conclusion