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Library of Stan Models for Survival Analysis

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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’)


- 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 <>`_


Install survivalstan via pip:


pip install survivalstan


- Issue Tracker:
- Source Code:


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

Please submit an issue `github <>`_ or via `gitter <>`_


The project is licensed under the Apache 2.0 license.


`Documentation`_ is available online.

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