Fit parameters of a phenology model to validation data

Calculates the estimated phenophases for a given set of parameters and a specified model (be sure to match parameter and requirements with the model.

pr_fit_parameters(
  par = NULL,
  data,
  cost = rmse,
  model = "TT",
  method = "GenSA",
  lower,
  upper,
  control,
  ...
)

Arguments

par: a vector of starting parameter values (function specific)
data: nested data structure with validation data as returned by format_phenocam() or format_pep725(), or your own dataset adhering to the same data structure.
cost: the cost function to use in the optimization, it should return a RMSE or other value which needs to be minimized
model: the model name to be used in optimizing the model
method: optimization method to use (default = GenSA) - GenSA : Generalized Simulated Annealing algorithm - genoud : GENetic Optimization Using Derivatives - BayesianTools: various bayesian based optimization tools
lower: lower limit of parameter values (function specific)
upper: upper limit of parameter values (function specific)
control: optimization control parameters (default = NULL)
...: extra arguments to pass to the function, mostly BayesianTools


if (FALSE) {
estimate <- pr_fit_parameters(par,data,model)

# estimate will return the best estimated parameter set given the
# validation data
}