roliveros-ramos/calibrar: Automated Parameter Estimation for Complex Models

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 'stats::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.

Getting started

Package details

Maintainer
LicenseGPL-2
Version0.9.0.9000
URL https://roliveros-ramos.github.io/calibrar/
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("roliveros-ramos/calibrar")
roliveros-ramos/calibrar documentation built on March 15, 2024, 12:08 a.m.