estimate_classical_wrapper: Internal wrapper for classical estimation of individuals

In dRiftDM: Estimating (Time-Dependent) Drift Diffusion Models

Internal wrapper for classical estimation of individuals

Description

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.

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.

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

See Also

estimate_classical(), estimate_dm()

dRiftDM documentation built on Dec. 1, 2025, 5:08 p.m.