Survivalstan¶

Survivalstan is a library of Survival Models written in Stan

It also contains a number of utility functions helpful when doing survival analysis.

Typical usage:

import survivalstan
# .. prep your data
fit1 = survivalstan.fit_stan_survival_model(...)
survivalstan.utils.plot_stan_summary([fit1], metric=’Rhat’)
survivalstan.utils.plot_coefs([fit1])

Features¶

Variety of standard survival models
- Weibull, Exponential, and Gamma parameterization
- A variety of semi-parametric and non-parametric baseline hazards
- Supports time-varying-coefficients
- Estimate time-varying effects
- Varying-effects by group
Extensible framework - bring your own Stan code, or edit the models provided
Uses pandas data frames & patsy formulas
Graphical posterior predictive checking
Plot posterior estimates of key parameters using seaborn
Annotated posterior draws of parameter estimates, as pandas dataframes
Supports caching via stancache or pystan-cache

Installation¶

Install survivalstan via pip:

pip install survivalstan

Contribute¶

Issue Tracker: http://github.com/hammerlab/survivalstan/issues
Source Code: http://github.com/survivalstan/survivalstan

Support¶

If you are having issues or questions, please let us know.

Please submit an issue github or via gitter

License¶

The project is licensed under the Apache 2.0 license.

Documentation¶

`Documentation http://jburos.github.io/survivalstan`_ is available online.