Metadata-Version: 2.1
Name: kwnpeb
Version: 0.1.11
Summary: Compute the Kiefer-Wolfowitz nonparametric maximum likelihood estimator
Home-page: https://github.com/sit836/KW_NPEB
Author: Sile Tao, Li Zhang, Guanqi Huang
Author-email: sile@ualberta.ca, lzhang2@ualberta.ca, frank.huangguanqi@gmail.com
License: UNKNOWN
Description: # Kiefer-Wolfowitz Nonparametric Empirical Bayes
        Compute the Kiefer-Wolfowitz nonparametric maximum likelihood estimator for mixtures. 
        
        In contrast to the previous approaches, the optimization problem is reformulated into a convex problem by 
        [Koenker and Mizera (2014)](http://www.stat.ualberta.ca/~mizera/Preprints/brown.pdf)'s method and efficiently solved by 
        interior-point method.
        
        ## Making Predictions With No Features - A Basic Usage
        Given a training set T = {y_i}, the algorithm provides a way to construct a predictor of future y-values such that the sum 
        of squared errors between observations and predictors is minimized.  
        
        ## Getting Started
        ### Prerequisites 
        You will need:
        * python (>= 3.6)
        * pip (>= 19.0.3)
        * MOSEK (>=8.1.30) 
        
        Important about MOSEK:
        * MOSEK is a commercial optimization software. Please visit [MOSEK](https://www.mosek.com/) for license information.
        * PIP: 
        ```
        pip install -f https://download.mosek.com/stable/wheel/index.html Mosek --user
        ``` 
        For different ways of installation, please visit their [installation page](https://docs.mosek.com/8.1/pythonapi/install-interface.html).
        * MOSEK needs to be installed in the GLOBAL environment. 
         
        
        
        ### Installing
        ```
        pip install kwnpeb
        ```
        
        ## Examples
        * [simple](https://github.com/sit836/KW_NPEB/tree/master/examples/simple) - The basic usage
        * [bayesball](https://github.com/sit836/KW_NPEB/tree/master/examples/bayesball) - In-season prediction of batting averages with the 2005 Major
        League baseball
        
        ## Contributors
        * [Sile Tao](https://ca.linkedin.com/in/sile-tao-95523941)
        * [Li Zhang](https://ca.linkedin.com/in/li-zhang-0350833b)
        * [Guanqi Huang](https://ca.linkedin.com/in/guanqi-huang)
        
        ## License
        This project is licensed under the MIT License - see the [LICENSE.md](LICENSE.md) file for details
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
