summary.drift_dm: Summary for 'drift_dm' objects

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

Summary for drift_dm objects

Description

summary and corresponding printing methods for objects of class drift_dm, created by a call to drift_dm().

Usage

## S3 method for class 'drift_dm'
summary(object, ...)

## S3 method for class 'summary.drift_dm'
print(x, ..., round_digits = drift_dm_default_rounding())

Arguments

object	an object of class drift_dm.
...	additional arguments passed forward (currently not used).
x	an object of class summary.drift_dm.
round_digits	integer, specifying the number of decimal places for rounding in the printed summary. Default is 3.

Details

summary.drift_dm() constructs a summary list with information about the drift_dm object. The returned list has class summary.drift_dm and can include the following entries:

• class: Class vector of the drift_dm object.

• summary_flex_prms: Summary of the flex_prms object in the model (see summary.flex_prms).

• prms_solve: Parameters used for solving the model (see prms_solve).

• solver: Solver used for generating model predictions.

• b_coding: Boundary coding for the model (see b_coding).

• obs_data: Summary table of observed response time data, if available, by response type (upper/lower boundary). rows correspond to upper first then lower responses; row names are prefixed by the boundary names from b_coding. columns (all lower-case) are: min, ⁠1st qu.⁠, median, mean, ⁠3rd qu.⁠, max, and n.

• cost_function: Name (or descriptor) of the cost function used during estimation.

• fit_stats: Fit statistics, if available. we return a named atomic vector created via unlist(unpack_obj(calc_stats(..., type = "fit_stats"))).

• estimate_info: Additional information about the estimation procedure.

print.summary.drift_dm() displays this summary in a formatted way.

Value

summary.drift_dm() returns a list of class summary.drift_dm (see details for the entries).

print.summary.drift_dm() returns invisibly the summary.drift_dm object.

Examples

# get a pre-built model for demonstration
a_model <- dmc_dm()
sum_obj <- summary(a_model)
print(sum_obj, round_digits = 2)

# more information is provided when we add data to the model
obs_data(a_model) <- dmc_synth_data # (data set comes with dRiftDM)
summary(a_model)

# fit indices are added once we evaluate the model
a_model <- re_evaluate_model(a_model)
summary(a_model)

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