A Python implementation of Scholz, Calbert & Smith (2011), an attempt to replicate Bruce Bueno de Mesquita's expected utility model for political forecasting.

Original: https://github.com/jmckib/bdm-scholz-expected-utility-model

Changes by David Masad:

• Update to Python 3
• Make terminal output optional
• Enable logging to file

• bdm_scholz_model.py: The model code itself.
• ExampleActors.csv: Actors from the Scholz et al. paper
• Sultan.csv: Actors from the 'Sultan' dataset (1997?)
• Example.log: Model output generated by running the model with the ExampleActors.csv actors.
• Example Analysis.ipynb: Jupyter Notebook demonstrating running the model interactively, and showing a sensitivity analysis.

usage: python bdm_scholz_model.py [-h] [--verbose] [--log LOG] csv_path num_rounds

positional arguments:

csv_path: Path to csv with input data

num_rounds: Number of rounds of simulation to run

optional arguments:

-h, --help: show this help message and exit

--verbose: Output the model dynamics to the terminal.

--log: Path to log the model run to.

example:

python bdm_scholz_model.py ExampleActors.csv 10 --verbose --log Example.log