Changelog

Source: NEWS.md

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.

calibrar 0.3

• 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 getObservedData() are deprecated and replaced by calibration_setup(), calibration_objFn() and calibration_data().
• spline_par() function to simplify the estimation of smooth time-varying parameters.

calibrar 0.2

• par argument for the calibrate function can be a list
• optimization methods from optimx, stats::optim and cmaes can be used
• several minor bugs fixed

calibrar 0.1

• First release