# BayesianExperiments.jl

`BayesianExperiments.jl`

provides a toolbox for running various types of Bayesian AB testing experiments.

Current features include:

- Hypothesis testing with Bayes factor. Support the effect size model with Normal distribution prior and JZS prior.
- Bayesian decision making with conjugate prior models. Support expected loss and probability to beat all as the stopping rule.
- Flexible experiment design for both fixed horizon experiments and sequential test experiment.
- Efficient simulation tools to support power analysis and sensitivity analysis.

## Documentation and Examples

For usage instructions and tutorials, see documentation.

For detailed discussions on many topics in the field, see the Jupyter notebooks in the `examples`

folder:

- Sequential Experiment with Two Models
- Type S Error in Fixed Horizon and Sequential Test Experiment
- Bayes Factor Experiment with Optional Stopping

Or you can go to binder to directly play with the Jupyter notebooks.

## Related Projects

Open source projects in R related to our project: