Package index • calibrar

Main functions

Functions for general purpose optimization, with support for parallel computation of derivatives.

calibrate(): Sequential parameter estimation for the calibration of complex models

optim2(): General-purpose optimization with parallel numerical gradient computation

optimh(): General-purpose optimization using heuristic algorithms

ahres(): Adaptative Hierarchical Recombination Evolutionary Strategy (AHR-ES) for derivative-free and black-box optimization

gradient(): Numerical computation of the gradient, with parallel capabilities

calibrar-package calibrar: Automated Calibration for Complex Models

Setting up a calibration

Functions to easily setup a new calibration for a complex model, from an R function running the model.

calibration_data(): Get observed data for the calibration of a model

calibration_objFn(): Create an objective function to be used with optimization routines

calibration_setup(): Get information to run a calibration using the calibrar package.

objFn() fitness(): Calcuted error measure between observed and simulated data

calibrar_demo(): Demos for the calibrar package

Parameter modelling

Functions to easily parametrize a model.

gaussian_kernel(): Calculate a discretization of the 2D Gaussian Kernel

spline_par(): Predict time-varying parameters using splines.

Test optimization functions

sphereN(): Sphere function with random noise

Auxiliar functions

.get_command_argument(): Get an specific argument from the command line

.read_configuration(): Read a configuration file.

Defunct functions

getObservedData() getCalibrationInfo() createObjectiveFunction(): Defunct functions in package calibrar.