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Internal wrapper for classical estimation of individuals

Source: R/core_estimate.R
estimate_classical_wrapper.Rd

This function wraps estimate_classical() to handle fitting multiple individuals in a consistent way. It prepares the data, distributes the estimation across individuals, and manages parallelization strategies and progress reporting. Unlike the deprecated estimate_model_ids(), this function no longer saves results to disk — instead, it directly returns an object of class fits_ids_dm.

Usage

estimate_classical_wrapper(
  drift_dm_obj,
  obs_data_ids,
  parallelization_strategy = NULL,
  progress = NULL,
  start_vals = NULL,
  optimizer,
  n_cores = NULL,
  seed = NULL,
  ...
)

Arguments

drift_dm_obj

a drift_dm object that will be estimated for each individual in obs_data_ids.

obs_data_ids

a data.frame of observed data including an ID column that uniquely identifies each individual.

parallelization_strategy

an integer, either 1 or 2. Strategy 1 parallelizes across individuals, while strategy 2 parallelizes within individuals (only supported for "DEoptim"). Default is 1

progress

an integer, controlling progress output. 0 = no progress, 1 = minimal output, 2 = progress bar. Default is 1

start_vals

an optional data.frame with starting values for each individual. Must contain an ID column matching the IDs in obs_data_ids, and one column per parameter.

seed

an optional seed to make the results reproducible

...

further arguments passed to estimate_classical(), including lower, upper, verbose, control, round_digits. Note that the argument return_runs is not supported.

Value

an object of class fits_ids_dm, which is a list with two components:

  • drift_dm_fit_info — a list containing the model object, observed data, optimizer information, and convergence messages

  • all_fits — a list of individual estimation results

Details

Convergence issues are checked automatically. If one or more individuals fail to converge, a warning is issued with the corresponding IDs and messages returned by the optimizer.

See also

estimate_classical(), estimate_dm()