Package: calibrar 0.9.0.9004

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.

Authors:Ricardo Oliveros-Ramos [aut, cre]

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calibrar/json (API)

# Install 'calibrar' in R:
install.packages('calibrar', repos = c('https://roliveros-ramos.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/roliveros-ramos/calibrar/issues

Pkgdown site:https://roliveros-ramos.github.io

On CRAN:

modelingoptimizationoptimization-methods

5.05 score 7 stars 27 scripts 271 downloads 19 exports 30 dependencies

Last updated 8 days agofrom:57e8cd91ba. Checks:8 ERROR. Indexed: yes.

TargetResultLatest binary
Doc / VignettesFAILFeb 13 2025
R-4.5-winERRORFeb 13 2025
R-4.5-macERRORFeb 13 2025
R-4.5-linuxERRORFeb 13 2025
R-4.4-winERRORFeb 13 2025
R-4.4-macERRORFeb 13 2025
R-4.3-winERRORFeb 13 2025
R-4.3-macERRORFeb 13 2025

Exports:.get_command_argument.read_configurationahrescalibrar_democalibratecalibration_datacalibration_objFncalibration_setupcreateObjectiveFunctionfitnessgaussian_kernelgetCalibrationInfogetObservedDatagradientobjFnoptim2optimhsphereNspline_par

Dependencies:BBclicmaescodetoolsDEoptimdfoptimforeachGenSAglueiteratorslbfgsb3clifecyclemagrittrminqanloptrnumDerivoptimxorepracmapsoquadprogRcppRcppArmadilloreportrrgenoudrlangsomastringistringrvctrs