Metadata-Version: 2.1
Name: py_countreg
Version: 0.0.1
Summary: Regression Models for Count Outcomes
Home-page: https://github.com/statcompute/py_countreg
Author: WenSui Liu
Author-email: liuwensui@gmail.com
License: UNKNOWN
Description: #### Introduction
        
        The package py\_countreg is a collection of functions to estimate various regression models for count outcomes.
        
        It is an ongoing project. More functionalities will come later.
        
        #### Core Functions
        
        ```
        Count Outcome Regressions
          |
          |-- Equi-Dispersion (Baseline)
          |     |
          |     `-- stdpoisson() : Standard Poisson 
          |
          |-- Over-Dispersion
          |     |
          |     |-- negbinom2()  : Negative Binomial (NB-2)
          |     |
          |     |-- hdlnegbin2() : Hurdle Negative Binomial (NB-2)
          |     |
          |     |-- zifnegbin2() : Zero-Inflated Negative Binomial (NB-2)
          |     |
          |     `-- zifpoisson() : Zero-Inflated Poisson 
          |
          `-- Over- and Under-Dispersions
                |
                |-- hdlpoisson() : Hurdle Poisson 
                |
                |-- genpoisson() : Generalized Poisson
                |
                `-- compoisson() : Conway-Maxwell Poisson 
        ```
        
        #### Reference
        
        WenSui Liu and Jimmy Cela (2008), Count Data Models in SAS, Proceedings SAS Global Forum 2008, paper 371-2008.
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
