Major changes
* Now, hBayesDM has both R and Python version, with same models included!
You can run hBayesDM with a language you prefer!
* Models in hBayesDM are now specified as YAML files. Using the YAML files,
R and Python codes are generated automatically. If you want to contribute
hBayesDM by adding a model, what you have to do is just to write a Stan file
and to specify its information! You can find how to do in the hBayesDM wiki
(https://github.com/CCS-Lab/hBayesDM/wiki).
* Model functions try to use parameter estimates using variational Bayesian
methods as its initial values for MCMC sampling by default (96). If VB
estimation fails, then it uses random values instead.
* The `data` argument for model functions can handle a data.frame object (2, 98).
* `choiceRT_lba` and `choiceRT_lba_single` are temporarily removed since their codes
are not suitable to the new package structure. We plan to re-add the models
in future versions.
* The Cumulative Model for Cambridge Gambling Task is added (`cgt_cm`; 108).
Minor changes
* The `tau` parameter in all models for the risk aversion task is modified to
be bounded to [0, 30] (77, 78).
* `bart_4par` is fixed to compute subject-wise log-likelihood (82).
* `extract_ic` is fixed for its wrong `rep` function usage (94, 100).
* The drift rate (`delta` parameter) in `choiceRT_ddm` and `choiceRT_ddm_single` is
unbounded and now it is estimated between [-Inf, Inf] (95, 107).
* Fix a preprocessing error in `choiceRT_ddm` and `choiceRT_ddm_single` (95, 109).
* Fix `igt_orl` for a wrong Matt trick operation (110).