calibrar

General optimisation and specific tools for the parameter estimation (i.e. calibration) of complex models, including stochastic ones. It implements generic functions that can be used for fitting any type of models, especially those with non-differentiable objective functions, with the same syntax as base::optim. It supports multiple phases estimation (sequential parameter masking), constrained optimization (bounding box restrictions) and automatic parallel computation of numerical gradients. Some common maximum likelihood estimation methods and automated construction of the objective function from simulated model outputs is provided. See https://roliveros-ramos.github.io/calibrar/ for more details.

Last 30 days

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.