Connectionists: ANN: HDDM 0.4 released.

[Thomas Wiecki]

We are very excited to announce the release of HDDM 0.4 with many new
features.

About:
HDDM is a python software package that implements Hierarchical Bayesian
parameter estimation of Drift Diffusion Models (via PyMC).

Homepage (with installation instructions):
http://ski.clps.brown.edu/hddm_docs/

Release notes:
HDDM 0.4 is now distributed under the simplified BSD license (see the
LICENSE file) instead of GPLv3.

New features
------------------

* Handling of outliers via mixture model.
  http://ski.clps.brown.edu/hddm_docs/howto.html#deal-with-outliers
* New model HDDMRegression to allow estimation of trial-by-trial
  regressions with a covariate.
  http://ski.clps.brown.edu/hddm_docs/howto.html#estimate-a-regression-model
* New model HDDMStimulusCoding.
  http://ski.clps.brown.edu/hddm_docs/howto.html#code-subject-responses
* New model HLBA -- a hierarchical Linear Ballistic Accumulator model
(hddm.HLBA).
* Posterior predictive quantile plots (see
model.plot_posterior_quantiles()).

Regards,
The HDDM developers.
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