Metadata-Version: 2.1
Name: bayes-traj
Version: 1.1.4
Summary: bayes_traj
Home-page: https://github.com/acil-bwh/bayes_traj
Author: James Ross
Author-email: jross@bwh.harvard.edu
License: UNKNOWN
Description: # Introduction
        
        **bayes_traj** is a software package written in Python that provides
        routines for performing Bayesian trajectory
        modeling of longitudinal data. Multiple, longitudinally observed target
        variables -- continuous, binary, or a combination -- can be modeled
        simultaneously. Per-trajectory random effects can also be modeled for
        continuous target variables. This package also provides command-line tools
        that facilitate spefication of Bayesian priors, enable visualization
        of trajectory modeling results, and compute summary and model
        fit statistics. 
        
        # Installation
        
        In order to install the package, type the folowing in the terminal:
        
            $ pip install bayes_traj
        
        # Overview
        
        **bayes_traj** provides several command-line tools: 
        
        * `generate_prior` -- used to speficy Bayesian priors for use the trajectory
          modeling
        * `viz_data_prior_draws` -- provides visualization of random draws from the
          prior
        * `bayes_traj_main` -- performs Bayesian trajectory modeling using a prior file
        * `viz_model_trajs` -- provides visualization of trajectories fit using
          `bayes_traj_main`
        * `sumarize_traj_model` -- prints model summary and fit statistics given a model
          file produce by `bayes_traj_main`
        * `assign_trajectory` -- writes a data file with appended trajectory assignment
          information given an input data file and a model file generated by the
          `bayes_traj_main` tool  	     
        
        Each of these tools can be run with the -h flag for additional usage information.
        
        For additional documentation, see https://acil-bwh.github.io/bayes_traj/index.html
        
        # Tests
        
        To run all unit tests, type the following in the package root directory:
        
            $ pytest
        
        
        # Contribute
        
        Please read our [contribution guidelines](./CONTRIBUTING.md).
        
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Build Tools
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Description-Content-Type: text/markdown
