calibrar - v0.9

calibrar 0.9

• new optim2() equivalent to stats::optim() but with parallel computation of numerical gradients.
• new optimh() wrapping heuristic methods with the same syntax of stats::optim().
• the calibrate() function implements the restart functionality for the Rvmmin method too, useful for the optimization of deterministic functions with long runtime.
• Improved methods for visualization of results.
• All optimization methods available in calibrate() can use functions reading and writing from the disk.
• Functioncalibrate() can use a different method for each estimation phase.
• calibrate() is a generic now.

• Automatic stopping criteria for the AHR-ES method:

    - 0: maxit/maxgen only
    - 1: 1 OR max step reduction
    - 2: relative tolerance on value (smoothing for AHR-ES)
    - 3: maximum number of generations without improvement of `reltol`.
  

• Automatic testing using testthat package.

• Automatic support to optimize functions produced with the TMB package, via a method for calibrate().

• getCalibrationInfo(), createObjectiveFuction() and getObservedData() are defunct now.

- R
Published by roliveros-ramos about 2 years ago

calibrar - v0.3

calibrar v0.3.0

• new optimization methods available in calibrate(): 'LBFGSB3', 'hjn', 'CMA-ES', 'genSA', 'DE', 'soma', 'genoud', 'PSO', 'hybridPSO', 'mads'.
• fine control of numerical gradient computations, including parallelization.
• replicates argument for stochastic functions
• several minor bugs fixed
• getCalibrationInfo(), createObjectiveFuction() and getObserved() data are replaced and deprecated and replaced by calibration_setup(), calibration_objFn() and calibration_data().
• spline_par() function to simplify the estimation of smooth time-varying parameters.
• several minor bugs fixed

This version can be installed from the osmose-model drat repository:

install.packages("calibrar", repo="https://osmose-model.github.io/drat/")

- R
Published by roliveros-ramos about 2 years ago

calibrar - v0.2.0

calibrar v0.2.0

First version available at CRAN: https://cran.r-project.org/web/packages/calibrar/index.html - Handles lists as parameter argument. - 18 optimization methods available now.

Automated parameter estimation for complex (ecological) models in R. This package allows the parameter estimation or calibration of complex models, including stochastic ones. It is a generic tool that can be used for fitting any type of models, especially those with non-differentiable objective functions. It supports multiple phases and constrained optimization. It implements maximum likelihood estimation methods and automated construction of the objective function from simulated model outputs.

- R
Published by roliveros-ramos about 10 years ago

calibrar - First release

Calibration of Ecological using Evolutionary Algorithms

The calibration of complex ecological models is a challenging optimization task, with a notable lack of tools for the calibration of stochastic models. The _calibrar_ package is a new R package for the calibration of stochastic ecological models, including Individual Based Models (IBMs). It is a generic tool that can be used for any type of model, especially those with non-differentiable objective functions. _calibrar_ supports multiple phase calibrations and constrained optimization. It implements maximum likelihood estimation methods and automated construction of the objective function from simulated model outputs.

- R
Published by roliveros-ramos over 11 years ago