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bayesian-psych

A library for easy creation of bayesian decision making models and classifiers

Availible Models:

  • Inter Temporal Choice Heuristics (ITCH)
  • Exponential Discounting
  • Hyperbolic Discounting
  • Quasi-Hyperbolic Discounting

Quick Example

Coming Soon

Data Column Meaning

Column Meaning
1-p1 one minus "more certain" outcome
1-p2 one minus "less certain" outcome
LL TRUE = choose Larger Later reward FALSE = choose Smaller Sooner Reward
df_num convenience variable distinguish each subject, discounting, reward case
discount_type discount-type (i.e. time, probability, or effort)
e1 smaller effort level
e2 larger effort level
is_test TRUE = data is part of testing set FALSE = data is part of training set
key participant number + discount_type + reward_type
participant participant number
reward_type reward-type (i.e. social, health, money)
t1 smaller time delay
t2 larger time delay
x1 smaller reward
x2 larger reward
t1_n smaller time delay normalized
t2_n larger time delay normalized
x1_n smaller reward normalized
x2_n larger reward normalized

Installation

git clone https://github.com/mhamilton723/bayesian-psych.git
cd bayesian-psych/src
python 2_model_comparison.py

If you encounter errors, pip install the required packages. Run the code in the numerical order provided. You do not need to run 1_parse_raw_data.py since the full data set cannot be made publically available due to Institutional Review Board and HIPAA Privacy Rules.

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A library for comparing and developing Bayesian models of human decision making

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