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calmr 0.8.1

• Minor patch for ggplot2 v4.0.0 compatibility.

calmr 0.8.0

• Major changes
  • Added CalmrModel class.
    • This class is contains information about the model, including, among other things, its name, (current) parameters, default_parameters, and several lists pointing to internal functions used to name, parse, and plot results. See help("CalmrModel-class") for more information on the slots.
    • Model logic is now encapsulated within the run() method (see help("run,CalmrModel-method")). This method modifies the CalmrModel to populate the .last_raw_results slot with lists of raw results, and overwrite internals such as model parameters.
    • The class has its own methods (including plot() and graph()). See ?CalmrModel-methods for more information.
  • Users can now define custom models by inheriting from CalmrModel class.
• Minor changes
  • Removed CalmrResults class. Raw and parsed results are now stored in the CalmrModel class’ .last_raw_results and .last_parsed_results slots, respectively. Aggregated results are now stored in the CalmrExperiment class’ results slot.
  • Added CalmrExperiment slot models to store the CalmrModel instances used in the experiment.
  • Added functionality to resume training a model across different experiments. If necessary, the objects representing the internal states of a model (e.g., a matrix of associations) will be expanded to accommodate new stimuli. This feature should be treated as experimental, and casual users should instead specify different phases in a single experiment.
  • Model definition now includes global flag for each parameter (is_global).
• Minor bug fixes:
  • Fixed bug in Witnauer’s comparator procedure form SM2007 for higher order comparisons.

calmr 0.7.1

• Fixed bug in usage of beta parameters in the RW1972 model. Added tests for all model parameters. Additionally, disabled functional stimuli for RW1972.
• Fixed bug in calculation of alpha deltas for MAC1975. Added tests for all model parameters and some expected behaviours with regards to associability.

calmr 0.7.0

• Corrected some issues in directional models.
• Created a vignette to expose the behaviour of directional models.
• Removed randomization column requirement from designs. Randomization of phases is now specified using the “!” character anywhere in the phase string. Using the old format throws a deprecation warning.
• Added support for seed experiment generation in make_experiment().
• Added set_calmr_palette() function to control the colour/fill scales used to plot results (#1).
• Added filter() method for CalmrExperiment class that allows filtering of aggregated data (#1).
• Fixed bug in make_experiment() that was triggered by empty phases and no miniblocks.
• Changed get_timings() to require a specific model name.
• Added vignette for TD model.

calmr 0.6.2

• Aggregation of ANCCR data now ignores time; time entries are averaged.
• Added the Temporal Difference model under the name “TD”. The model is in an experimental state.
• Experiments for time-based models now require a separate list to construct time-based experiences. See get_timings().
• Added experiences<-, timings, timings<- methods for CalmrExperiment class.
• Revamped plotting functions and parsing functions.
• Revamped output names for all models to make them more intelligible.
• Fixed a bug related to the aggregation of pools in HDI2020 and HD2022.
• Consolidated some man pages.

calmr 0.6.1

• Added outputs argument to run_experiment(), parse(), and aggregate(), allowing the user to parse/aggregate only some model outputs.
• Documentation corrections for CRAN resubmission.

calmr 0.6.0

• Added dependency on data.table resulting in great speedups for large experiments.
• Replaced dependency on cowplot with dependency on patchwork.
• Removed dependencies on tibble, dplyr, tidyr, and other packages from the tidyverse.
• Removed shiny app from the package.
• The previous app is now distributed separately via the calmr.app package available on GitHub.
• Test coverage has reached 100%.
• The package is now ready for CRAN submission.

calmr 0.5.1

• Added parallelization and progress bars via future, future.apply, and progressr.
• Function calmr_verbosity can set the verbosity of the package.

calmr 0.5.0

• Implementation of ANCCR (Jeong et al., 2022), the first time-based model included in calmr.
• Added parameter distinction between trial-wise and period-wise parameters.
• Added internal augmentation of arguments depending on the model.
• All trial-based models do not use pre/post distinctions anymore. Using the “>” special character does not affect these models anymore.
• The “>” special character is used to specify periods within a trial. For example, “A>B>C” implies A is followed by B which is followed by C. See the using_time_models vignette for additional information.
• Named stimuli now support numbers trailing characters (e.g., “(US1)” is valid now.)

calmr 0.4.0

• Major refactoring of classes and models. This should help development moving forward.
• Added several methods for access to CalmrExperiment contents, including c (to bind experiments) results, plot, graph, design, and parameters.
• Created CalmrDesign and CalmrResults classes.
• Rewrote parsers to be less verbose and to rely less on the tidyverse suite and piping.
• Substantially reduced the complexity of make_experiment function (previous make_experiment).
• Introduced distinction between stimulus-specific and global parameters.
• Parameters are now lists instead of data.frames.
• Modified UI for calmr app to include a sidebar.
• Simplified the app by removing some of the options.
• Nearly duplicated the number of tests.

calmr 0.3.0

• Added first version of the SOCR model (SM2007) as well as two vignettes explaining the math behind the implementation and some quick simulations.
• Documentation progress.

calmr 0.2.0

• Added multiple models to package and app (RW1972, PKH1982, MAC1975).
• Implementation of basic S4 classes for model, experiment, fit, and RSA comparison objects, as well as their methods.
• Added genetic algorithms (via GA) for parameter estimation.
• Added basic tools to perform representational similarity analysis.
• Documentation progress.

calmr 0.1.0

• heidi is now calmr. The package now aims to maintain several associative learning models and implement tools for their use.
• Major overhaul of the training function (train_pav_model). All relevant calculations are now done as a function of all functional stimuli instead of just the US.
• Support for the specification of expectation/correction steps within the trial via “>”. For example, the trial “A>(US)” will use only A to generate the expectation, but will learn about both stimuli during the correction step.
• The previous plotting function for R-values has been revamped to allow both simple and complex versions. The complex version facets r-values on a predictor basis, and uses colour lines for each target.
• Bugfix related to stimulus saliencies.

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They may not be fully stable and should be used with caution. We make no claims about them.
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