Providing the Tracy-Widom distribution functions for beta = 1, 2, or 4 in Python.
This package uses the interpolation tables in
- Bejan, Andrei Iu. (2005), Largest eigenvalues and sample covariance matrices. Tracy–Widom and Painleve II: Computational aspects and realization in S-Plus with applications, M.Sc. dissertation, Department of Statistics, The University of Warwick.
and the asymptotics in
- Borot, Gaëtan and Nadal, Céline (2012), Right tail expansion of Tracy-Widom beta laws, Random Matrices: Theory and Applications Vol. 01, No. 03, 1250006. (arXiv:1111.2761)
This package is MIT licensed. If you use this package in your work, please consider citing the above publications and listing the URL of this package (https://github.com/yymao/TracyWidom/).
You can install tracywidom via conda or pip:
# Install via conda with the conda-forge channel
conda install tracywidom --channel conda-forge
# Or, install via pip
pip install tracywidomHere's an example of using the TracyWidom package.
import numpy as np
from TracyWidom import TracyWidom
x = np.linspace(-10, 10, 101)
tw1 = TracyWidom(beta=1) # allowed beta values are 1, 2, and 4
pdf = tw1.pdf(x)
cdf = tw1.cdf(x)
r = np.random.rand(1000)
tw1_sample = tw1.cdfinv(r)