Metadata-Version: 2.1
Name: chiscore
Version: 0.0.11
Summary: Test statistics from linear combination of chi-squared distributions.
Home-page: https://github.com/limix/chiscore
Author: Rachel Moore, Danilo Horta
Author-email: rm18@sanger.ac.uk, horta@ebi.ac.uk
Maintainer: Danilo Horta
Maintainer-email: horta@ebi.ac.uk
License: MIT
Download-URL: https://github.com/limix/chiscore
Description: # chiscore
        
        [![Travis](https://img.shields.io/travis/com/limix/chiscore.svg?style=flat-square&label=linux%20%2F%20macos%20build)](https://travis-ci.com/limix/chiscore) [![AppVeyor](https://img.shields.io/appveyor/ci/Horta/chiscore.svg?style=flat-square&label=windows%20build)](https://ci.appveyor.com/project/Horta/chiscore)
        
        Estimate the joint significance of test statistics derived from linear combination
        of chi-squared distributions.
        
        ## Install
        
        We recommend installing it via
        [conda](http://conda.pydata.org/docs/index.html):
        
        ```bash
        conda install -c conda-forge chiscore
        ```
        
        Alternatively, chiscore can also be installed using
        [pip](https://pypi.python.org/pypi/pip):
        
        ```bash
        pip install chiscore
        ```
        
        ## Running the tests
        
        After installation, you can test it
        
        ```bash
        python -c "import chiscore; chiscore.test()"
        ```
        
        as long as you have [pytest](https://docs.pytest.org/en/latest/).
        
        ## Usage
        
        ```python
        >>> from chiscore import davies_pvalue
        >>> q = 1.5
        >>> w = [[0.3, 5.0], [5.0, 1.5]]
        >>> davies_pvalue(q, w)
        {'p_value': 0.6151796819770086, 'param': {'liu_pval': 0.6151796819770086, 'Is_Converged': 1.0}, 'p_value_resampling': None, 'pval_zero_msg': None}
        ```
        
        ```python
        >>> from chiscore import mod_liu
        >>> q = 1.5
        >>> w = [0.3, 5.0]
        >>> mod_liu(q, w)
        (0.6230031759923031, 5.3, 7.083784299369935, 1.0071999066892092)
        ```
        
        ```python
        >>> from chiscore import optimal_davies_pvalue
        >>> q = [1.5, 3.0]
        >>> mu = -0.5
        >>> var = 1.0
        >>> kur = 3.0
        >>> w = [10.0, 0.2, 0.1, 0.3]
        >>> remain_var = 0.5
        >>> df = 3.4
        >>> trho = [5.1, 0.2]
        >>> grid = [0., 0.01]
        >>> optimal_davies_pvalue(q, mu, var, kur, w, remain_var, df, trho, grid)
        0.966039962464624
        ```
        
        ## Authors
        
        * [Danilo Horta](https://github.com/horta)
        
        ## License
        
        This project is licensed under the [MIT License](https://raw.githubusercontent.com/limix/chiscore/master/LICENSE.md).
        
Keywords: test statistic,chi-squared distribution,p-value
Platform: Windows
Platform: MacOS
Platform: Linux
Classifier: Development Status :: 5 - Production/Stable
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Description-Content-Type: text/markdown
