Skip to main content

Linear combination of independent noncentral chi-squared random variables

Project description

chi2comb

Travis AppVeyor

Install

The recommended way to install this package is via conda

conda install -c conda-forge chi2comb

Alternatively, it can be installed using the pip command

pip install chi2comb

Usage

>>> from chi2comb import chi2comb_cdf, ChiSquared
>>>
>>> gcoef = 0.0
>>> ncents = [0, 0, 0]
>>> q = 1
>>> dofs = [1, 1, 1]
>>> coefs = [6, 3, 1]
>>> chi2s = [ChiSquared(coefs[i], ncents[i], dofs[i]) for i in range(3)]
>>> result, errno, info = chi2comb_cdf(q, chi2s, gcoef)
>>> result
0.054212946675253226
>>> errno
0
>>> info
Info(emag=0.7623482489861554, niterms=744, nints=2, intv=0.03819311576613404, truc=53.37968999861114, sd=0.0, ncycles=51)

Problems

If you encounter any issue, please, submit it.

Authors

License

This project is licensed under the MIT License.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

chi2comb-0.0.2.tar.gz (6.9 kB view hashes)

Uploaded Source

Built Distributions

chi2comb-0.0.2-cp37-cp37m-win_amd64.whl (21.4 kB view hashes)

Uploaded CPython 3.7m Windows x86-64

chi2comb-0.0.2-cp37-cp37m-manylinux1_x86_64.whl (22.1 kB view hashes)

Uploaded CPython 3.7m

chi2comb-0.0.2-cp37-cp37m-macosx_10_6_intel.whl (15.5 kB view hashes)

Uploaded CPython 3.7m macOS 10.6+ intel

chi2comb-0.0.2-cp36-cp36m-win_amd64.whl (21.4 kB view hashes)

Uploaded CPython 3.6m Windows x86-64

chi2comb-0.0.2-cp36-cp36m-manylinux1_x86_64.whl (22.1 kB view hashes)

Uploaded CPython 3.6m

chi2comb-0.0.2-cp36-cp36m-macosx_10_6_intel.whl (15.5 kB view hashes)

Uploaded CPython 3.6m macOS 10.6+ intel

chi2comb-0.0.2-cp27-cp27mu-manylinux1_x86_64.whl (25.2 kB view hashes)

Uploaded CPython 2.7mu

chi2comb-0.0.2-cp27-cp27m-manylinux1_x86_64.whl (25.2 kB view hashes)

Uploaded CPython 2.7m

chi2comb-0.0.2-cp27-cp27m-macosx_10_6_intel.whl (15.4 kB view hashes)

Uploaded CPython 2.7m macOS 10.6+ intel

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page