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.