ch02R_maize_parallel                  ch02. R introduction. Improving performance with parallel code for maize.model
ch03Simulation.exponential            ch03. Simulation. Exponential model. Comparison of numerical integration with analytical solution. Influence of time step on error of integration. Improved Euler integration method.
ch03Simulation.prey.predator          ch03. Simulation. Predator-Prey Lotka-Volterra model with deSolve integration library.
ch03Simulation.population.age         ch03. Simulation. Population dynamics model with a representation of population with age classes.
ch03Simulation.watbal                 ch03. Simulation. WaterBalance model.
ch03Simulation.maize                  ch03. Simulation. Maize model.
ch03Simulation.maize.muchow           ch03. Simulation. Maize model of Muchow with harvest index.
ch03Simulation.epirice                ch03. Simulation. Epirice model (up to 10 min).
ch03Simulation.zadoks                 ch03. Simulation. Zadoks model - SEIR for plant disease.
ch06USA_Magarey                       ch06. Uncertainty and Sensitivity analysis. Example on Magarey model
ch06USA_Weed                          ch06. Uncertainty and Sensitivity analysis. Example of Monte Carlo, Morris, Fast, Sobol and ANOVA for weed.model. Attention: run time can be long (up to 30 min).
ch06USA_Lactation                     ch06. Sensitivity analysis. Example on Lactation model.
ch06USA_Carcass                       ch06. Sensitivity analysis. Example on Carcass model. Morris.
ch08Bayes_Carbon                      ch08. Bayes. Example with carbonsoil.model
ch10maize1data                        ch10. Case study. Exploration of data.
ch10maize2evaluation                  ch10. Case study, Maize model. Evaluation.
ch10maize3uncertainty                 ch10. Case study, Maize model. Uncertainty analysis (may take up to 20 min).
ch10maize4sensitivity                 ch10. Case study, Maize model. Sensitivity analysis (may take up to 40 min).
ch10maize5aparameterOLS_gradient      ch10. Case study, Maize model. Parameter estimation with OLS and gradient method (may take up to 10 min)
ch10maize5bparameterOLS_simplex       ch10. Case study, Maize model. Parameter estimation with OLS simplex method (may take up to 120 min)
ch10maize5cparameterConcL             ch10. Case study, Maize model. Parameter estimation with concentrated likelihood - simplex method (may take up to 120 min)
ch10maize5dparameterConcL_log         ch10. Case study, Maize model. Parameter estimation with concentrated likelihood and a log transformation of variable - simplex method (may take up to 120 min)
ch10maize6aMSEP_OLS                   ch10. Case study, Maize model. Estimation of MSEP by cross-validation after OLS parameter estimation (may take up to 120 min)
ch10maize6bMSEP_ConcL                 ch10. Case study, Maize model. Estimation of MSEP by cross-validation after concentrated likelihood parameter estimation (may take up to 120 min)
ch10maize7scenario                    ch10. Case study, Maize model. Use of final model for multi-site multi-year simulations (may take a few minutes)
ch10maizeB5aBayesEstimRUE             ch10. Case study, Maize model. Parameter estimation using a Bayesian approach, using MCMC - only RUE is estimated (may take up to a few hours)
ch10maizeB5bBayesEstimAllparam        ch10. Case study, Maize model. Parameter estimation using a Bayesian approach, using MCMC - all parameters (may take up to 4-5 days for 30000 iterations and 2 chains)
ch10maizeB7BayesUncertainty           ch10. Case study Maize model. Use the posterior distribution for multi-site multi-year simulations. You must run ch10maizeB5bBayesEstimAllparam before this demo in the same session or adapt both scripts may take up to a few hours).
ch10maizeB7Bayes_functionsMH          ch10. Case study Maize model. Load specific functions for Bayesian approach. No calculation.
ch14maizeS8DataAssimilation           ch14. Data Assimilation on case study Maize model. Data assimilation using DLM (few minutes)
ch14DLM_WheatYieldGreece              ch14. Data Assimilation. Example of Dynamic Linear Model (DLM) for analyzing yield time series.
ch14DLM_CarbonSoil                    ch14. Data Assimilation. Example of Dynamic Linear Model (DLM) with carbonsoil.model.
ch14DLM_watbal                        ch14. Data Assimilation. Example of Dynamic Linear Model (DLM) with watbal.model.
