The purpose of CroptimizR is to provide functions for estimating crop model parameters from observations of their simulated variables, a process often referred to as calibration. For that, it offers a generic framework for linking crop models with up-to-date and ad-hoc algorithms, as well as a choice of goodness-of-fit criteria and additional features adapted to the problem of crop model calibration. It facilitates the comparison of different types of methods on different models. It is used in this context in the AgMIP Calibration project on a dozen of crop models.
The Get started page describes the main concepts and features of the package and details how to connect its own crop model to CroptimizR.
The list of functions accessible to the users is provided in the Reference tab.
If you want to be notified when a new release of this package is made, you can tick the Releases box in the “Watch / Unwatch => Custom” menu at the top right of this page.
Before installing the package, it is recommended to update all already
installed R packages. This can be done using the command
update.packages() or clicking on the Update button of the Packages
panel of Rstudio.
The latest released version of the package can be installed from GitHub using:
devtools::install_github("SticsRPacks/CroptimizR@*release")Or using the lightweight remotes package:
# install.packages("remotes")
remotes::install_github("SticsRPacks/CroptimizR@*release")-
Simple introductory examples of parameter estimation using CroptimizR on complex crop models are provided in vignettes, using the STICS model here and the ApsimX model here
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A more complex example, showing simultaneous estimation of specific and varietal plant parameters is available here.
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An example demonstrating the application of a parameter selection algorithm can be found here.
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An example using the DREAM-zs Bayesian algorithm is detailed here.
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An example illustrating the AgMIP calibration workflow is shown here.
See
here
for a detailed description of the input and output arguments of the
estim_param function, the core function for parameter estimation (or
type ? estim_param in an R console after installing and loading the
CroptimizR package). See also the run_protocol_agmip function for
applying the AgMIP calibration workflow in a streamlined way.
If you have any question or suggestion or if you want to report a bug, please do it via the GitHub issues.
Thanks for that, this would greatly help us to improve this package.
If you have used this package for a study that led to a publication or
report, please cite us. To get the suggested citation, run
citation("CroptimizR").