Merge pull request #89 from venpopov/update-news

Update NEWS.md" file with history of changes

NEWS.md

@@ -1,3 +1,61 @@
-# bmm (development version)
+# bmm 0.1.1+
 
-* Initial CRAN submission.
+### New features
+
+* New model available - The Signal Discrimination Model by Oberauer (2023) for visual working memory continuous reproduction tasks. See ?sdmSimple. The current version does not take into account non-target activation
+* Add ability to extract information about the default priors in `bmm` models with `get_model_prior()` (#53)
+* Add ability to generate stan code and stan data for each model with `get_model_stancode()` and `get_model_standata()` (#81)
+* BREAKING CHANGE: Add distribution functions for likelihood (e.g. `dimm()`) and random variate generation `rimm()`) for all models in the package. Remove deprecated `gen_3p_data()` and `gen_imm_data()` functions (#69)
+* Two new datasets available: `ZhangLuck_2008` and `OberauerLin_2017` (#22)
+
+### Documentation
+
+* Website for the development version of the package is now available at https://venpopov.github.io/bmm/dev/ (#18)
+* Add vignettes for each model to the website at https://venpopov.github.io/bmm/dev/articles/
+* Add a detailed developer's guide to the website at https://venpopov.github.io/bmm/dev/dev-notes (#21)
+* Improve README with more detailed information about the package's goals and its models (#21)
+
+### Other changes
+
+* Save `bmm` package version in the `brmsfit` object for reproducibility - e.g. `fit$version$bmm` (#88)
+
+
+# bmm 0.1.1
+
+### New features
+
+* BREAKING CHANGE: Improve user interface to fit_model() ensures package stability and future development. Model specific arguments are now passed to the model functions as named arguments (e.g. `mixture3p(non_targets, setsize)`). This allows for a more flexible and intuitive way to specify model arguments. Passing model specific arguments directly to the `fit_model()` function is now deprecated (#43).
+* Add information about each model such as domain, task, name, version, citation, requirements and parameters (#42)
+* Add ability to generate a template file for adding new models to the package with `use_model_template()` (for developers) (#39)
+
+### Other changes
+
+* Improve documentation of model functions. You can now get help on each model by typing `?model_name` into your console. For example, calling the information on the full version of the Interference Measurement Model would look like this: `?IMMfull`
+
+
+# bmm 0.1.0
+
+A major restructuring of the package to support stable and generalizable development of future models (#41). 
+
+### New Features
+
+* Refactor the `fit_model()` function to be generic and independent of the model being fit (#20)
+* Transform models to be S3 objects. (#41). 
+* View currently supported models with new function `supported_models()`. Currently supported models are: `mixture2p()`, `mixture3p()`, `IMMabc()`, `IMMbsc()`, `IMMfull()` 
+* Add S3 methods for checking the data, formula, model and priors (#41)
+* Add distribution functions for the Signal Discrimination Model. See `?SDM` for usage (#27)
+* Add softmax and invsoftmax functions 
+
+### Bug Fixes
+
+* Change default prior on log(kappa) to Normal(2,1) for the `mixture3p()` model (#15)
+
+### Other changes
+
+* BREAKING CHANGE: deprecate `model_type` argument in `fit_model()`. Models must now be specified with S3 functions passed to argument `model` rather than model names as strings passed to argument `model_type` (#41)
+* Add extensive unit testing
+
+
+# bmm 0.0.1
+
+* Initial release version