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Changelog

Source: NEWS.md

dRiftDM (development version)

dRiftDM 0.3.1

CRAN release: 2025-12-01

Minor

  • For type = "sep_b" in estimate_dm(): Chains are now initialized more robustly.

  • We reverted back to adding the value 0.001 to t_vec when evaluating DMC’s drift rate for a!=2 (after noticing solver crashes with the former value of 1e-5).

  • It is now possible to pass a value via ddm_opts() to objects of type dmc_dm(); this controls the value that is added to t_vec when evaluating DMC’s drift rate for a!=2.

dRiftDM 0.3.0

Important notes for users

  • The workflow for estimating a model has changed with the introduction of estimate_dm(). From this version onward, fits are not automatically saved to the file system to be reloaded later. Instead, estimate_dm() returns fitted objects directly, and you save the results yourselves.

Major and new features

  • dRiftDM now uses an adaptive time-stepping scheme for deriving PDFs — substantially increasing speed.

  • We now support variability in the drift rate for the constant drift-rate component (not only for the Ratcliff DDM).

  • plot() methods were redesigned to avoid argument clashes and to provide more customization options.

  • drift_dm() objects gain a new entry cost_function. This lets us use the "rmse" statistic or full-range maximum likelihood, and it enables fitting aggregated data via "rmse".

  • The neg_log_like entry of a drift_dm object has been replaced by the more general cost_value.

  • cost_function() accessor and replacement methods have been introduced.

  • cost_value() accessor and replacement methods have been introduced.

  • estimate_dm() has been introduced.

  • If possible, dRiftDM now provides reasonable starting values for the Nelder-Mead and BFGS optimization routines (both bounded and unbounded). To this end, EZ Diffusion parameter estimates are used whenever possible, in combination with grid-search-like procedure.

  • estimate_model() has been deprecated and superseded by estimate_dm().

  • estimate_model_ids() has been deprecated. Use estimate_dm(), which does not save individual fits to the file system — ensuring more consistent behavior across fitting modes.

  • get_lower_upper() has been introduced. It provides default upper and lower parameter ranges for pre-built models and their components.

  • Hierarchical and non-hierarchical Bayesian parameter estimation is now possible via estimate_dm()! This is still experimental, and the returned mcmc_dm type is not fully integrated yet (currently: diagnostic checks and parameter extraction is supported).

  • calc_stats() gains basic_stats and densities options for type. basic_stats returns means, standard deviations, and choice proportions; densities returns density values.

  • calc_stats() gains a resample option to quantify variability in model predictions. We can resample for a given model or a single individual, or bootstrap an entire sample.

  • calc_stats() arguments split_by_ID and average have been superseded by the more general level argument.

  • simulate_data() no longer returns RTs restricted to the time grid (step size dt). PDFs are linearly interpolated for inverse transform sampling. We can control RT decimal places via round_to.

  • simulate_data() now supports the conds argument.

  • ssp_dm() gains var_non_dec and var_start to toggle variability in non-decision time and starting point.

  • ssp_dm() now uses uniform variability in non-decision time, aligning more closely with the original publication.

  • ssp_dm() default dx and dt increase computation speed while balancing numerical error for many parameter values.

  • dmc_dm() default dx and dt increase computation speed while balancing numerical error for many parameter values.

  • ratcliff_dm() default dx and dt increase computation speed while balancing numerical error for many parameter values.

  • coef() and plot() now support the mcmc_dm object type.

  • check_discretization() has been introduced. This function helps us assess the loss in precision when increasing dt and dx.

  • get_example_fits_ids() was removed.

  • get_example_fits() has been introduced to obtain fits_ids_dm, fits_agg_dm, or mcmc_dm objects.

Minor

  • nt_constant() now uses round() instead of as.integer() to locate the Dirac delta index, reducing bias in non-decision time estimates.

  • pdfs() now also returns a vector of the time domain.

  • The coef() and plot() method now supports mcmc_dm objects.

  • The progress argument replaces verbose in calc_stats (default: 1).

  • The "fit_stats" option for calc_stats() now returns multiple fit statistics, including log-likelihood, AIC, BIC, and root-mean-squared error.

  • simulate_traces now properly considers trial-by-trial variability in the drift rate.

Bug and code fixes

  • calc_stats() is now more precise due to proper numerical integration.

dRiftDM 0.2.2

CRAN release: 2025-03-04

New features:

  • print() and summary() methods are now available for traces_dm, traces_dm_list, stats_dm, stats_dm_list, and coefs_dm objects.

  • New unpack_obj() makes it easy to strip away attributes and class labels of objects created by dRiftDM. The more specific predecessor function unpack_traces() is now deprecated unpack_traces().

  • New pdfs() provides access to a model’s predicted probability density function.

Minor improvements and changes:

  • coef.drift_dm() gains a select_custom_prms argument.

  • list_stats_dm objects are now called stats_dm_list for name consistency.

  • traces_dm objects now have additional attributes (which were required for appropriate print and summary methods).

  • More consistent capitalization in print.summary.*() methods.

dRiftDM 0.2.1

CRAN release: 2025-01-08

  • Initial CRAN submission.