Metadata-Version: 2.1
Name: sprcom
Version: 0.2
Summary: Bayesian spatial regression of communities
Home-page: UNKNOWN
Author: Christopher Krapu
Author-email: ckrapu@gmail.com
License: UNKNOWN
Download-URL: https://github.com/ckrapu/sprcom/archive/v0.1-beta.tar.gz
Description: # SpRCom
        
        
        <p align="center">
        <img src="https://github.com/ckrapu/sprcom/blob/master/data/animation.gif">
        </p>
        
        `sprcom` stands for **Sp**atial **R**egression of **Com**munities and is a statistical  package designed to streamline the interpretation and modeling of very high dimensional binary and count-valued data. The underlying model assumes a low-dimensional latent structure via communities or clusters that leads to a parsimonious model. `sprcom` can also account for the dependence of these communities on covariates! A number of utility and plotting functions are included to help visualize your results. `sprcom` is a wrapper for a [PyMC3](https://docs.pymc.io/) model and you can use any PyMC3 estimation method with it including Hamiltonian Monte Carlo and ADVI.
        
        ```python
        covariates, response, adjacency = load_data(...)
        n_communities = 5
        model = spatial_community_regression(covariates, response, adjacency,n_communities)
        with model:
          trace = pm.sample()
        ...
        ```
        
        
        
        We've included documentation to help you get up and running. Check out the `florabank1-tutorial` notebook for more details!
        
        For questions or comments please contact Christopher Krapu at `ckrapu@gmail.com`.
        
Platform: UNKNOWN
Description-Content-Type: text/markdown
