NEWS.md
In roliveros-ramos/calibrar: Automated Parameter Estimation for Complex Models

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.

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.