Test statistics from linear combination of chi-squared distributions.
Project description
chiscore
Estimate the joint significance of test statistics derived from linear combination of chi-squared distributions.
Install
We recommend installing it via conda:
conda install -c conda-forge chiscore
Alternatively, chiscore can also be installed using pip:
pip install chiscore
Running the tests
After installation, you can test it
python -c "import chiscore; chiscore.test()"
as long as you have pytest.
Usage
>>> 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}
>>> 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)
>>> 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
License
This project is licensed under the MIT License.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
chiscore-0.0.7.tar.gz
(41.5 kB
view hashes)