Hierarchical Bayesian Modeling of Decision-Making Tasks

Fit an array of decision-making tasks with computational models in a hierarchical Bayesian framework. Can perform hierarchical Bayesian analysis of various computational models with a single line of coding.


Dec 28, 2016 (

  1. Change
  • Add help files
  • Add a function for checking Rhat values (rhat).
  • Change a link to its tutorial website

Dec 21, 2016 (

  1. Change
  • Use wide normal distributions for unbounded parameters (gng_* models).
  • Automatic removal of rows (trials) containing NAs.

Sep 29, 2016 (

  1. Change
  • Add a function for plotting individual parameters (plotInd)

Sat July 16 2016 (0.2.3)

  1. Change
  • Add a new task: the Ultimatum Game
  • Add new models for the Probabilistic Reversal Learning and Risk Aversion tasks
  • ‘bandit2arm’ -> change its name to ‘bandit2arm_delta’. Now all model names are in the same format (i.e., TASK_MODEL).
  • Users can extract model-based regressors from gng_m* models
  • Include the option of customizing control parameters (adapt_delta, max_treedepth, stepsize)
  • ‘plotHDI’ function -> add ‘fontSize’ argument & change the color of histogram

Sat Apr 02 2016 (0.2.1)

  1. Bug fixes
  • All models: Fix errors when indPars=“mode”
  • ra_prospect model: Add description for column names of a data (*.txt) file
  1. Change
  • Change standard deviations of ‘b’ and ‘pi’ priors in gng_* models

Fri Mar 25 2016 (0.2.0) Initially released.

Reference manual

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0.4.0 by Woo-Young Ahn, 6 months ago


Browse source code at https://github.com/cran/hBayesDM

Authors: Woo-Young Ahn [aut, cre], Nate Haines [aut], Lei Zhang [aut]

Documentation:   PDF Manual  

GPL-3 license

Imports rstan, rstantools, loo, grid, parallel, mail, ggplot2

Depends on Rcpp, methods

See at CRAN