biomasse: The Winter Wheat Dynamic Model
In multisensi: Multivariate Sensitivity Analysis

Description Usage Arguments Details Value References

The Winter Wheat Dynamic Model, a toy model to illustrate the main multisensi methods

1	biomasse(input, climdata, annee = 3)

`input`	vector of input values.
`annee`	year.
`climdata`	a meteorological data.frame specific to biomasse.

The Winter Wheat Dry Matter model (WWDM) is a dynamic crop model running at a daily time step (Makowski et al, 2004). It has two state variables, the above-ground winter wheat dry matter U(t), in g/m^2 and the leaf area index LAI(t) with t the day number from sowing (t=1) to harvest (t=223). In the multisensi package implementation, the biomasse function simulates the output for only one parameter set (the first row of input if it is a matrix or a data.frame).

a vector of daily dry matter increase of the Winter Wheat biomass, over 223 days

Makowski, D., Jeuffroy, M.-H., Gu\'erif, M., 2004 Bayesian methods for updating crop model predictions, applications for predicting biomass and grain protein content. In: Bayesian Statistics and Quality Modelling in the Agro-Food Production Chain (van Boeakel et al. eds), pp. 57-68. Kluwer, Dordrecht

Monod, H., Naud, C., Makowski, D., 2006 Uncertainty and sensitivity analysis for crop models. In: Working with Dynamic Crop Models (Wallach D., Makowski D. and Jones J. eds), pp. 55-100. Elsevier, Amsterdam

multisensi documentation built on May 2, 2019, 2:14 p.m.