Re-evaluate the model

Updates the PDFs of a model. If observed data is available (e.g., via the obs_data entry or the stats_agg entry; depending on the cost_function, see also drift_dm()), the cost_value is also updated.

Usage

re_evaluate_model(drift_dm_obj, eval_model = TRUE)

Arguments

drift_dm_obj

an object of type drift_dm

eval_model

logical, indicating if the model should be evaluated or not. If FALSE, PDFs and the value of the cost function are deleted from the model. Default is True.

Value

Returns the passed drift_dm_obj object, after (re-)calculating the PDFs and (if observed data is set) the cost_value.

• the PDFs an be addressed via drift_dm_obj$pdfs

• the cost_value can be addressed via drift_dm_obj$cost_value

Note that if re_evaluate model is called before observed data was set, the function silently updates the pdfs, but not cost_value.

Details

More in-depth information about the mathematical details for deriving the PDFs can be found in Richter et al. (2023)

See also

drift_dm()

Examples

# choose a pre-built model (e.g., the Ratcliff model)
# and set the discretization as needed
my_model <- ratcliff_dm(t_max = 1.5, dx = .005, dt = .005)

# then calculate the model's predicted PDF
my_model <- re_evaluate_model(my_model)
str(my_model$pdfs) # show the structure of the attached pdfs
#> List of 1
#>  $ null:List of 2
#>   ..$ pdf_u: num [1:301] 1e-08 1e-08 1e-08 1e-08 1e-08 ...
#>   ..$ pdf_l: num [1:301] 1e-08 1e-08 1e-08 1e-08 1e-08 ...

# if you want the cost_function, make sure some data is attached to the
# model (see also the documentation of obs_data())
obs_data(my_model) <- ratcliff_synth_data # this data set comes with dRiftDM
my_model <- re_evaluate_model(my_model)
str(my_model$pdfs)
#> List of 1
#>  $ null:List of 2
#>   ..$ pdf_u: num [1:301] 1e-08 1e-08 1e-08 1e-08 1e-08 ...
#>   ..$ pdf_l: num [1:301] 1e-08 1e-08 1e-08 1e-08 1e-08 ...
print(my_model$cost_value)
#> [1] -191.6983