hyppo
hyppo (HYPothesis testing in PythOn, pronounced "hippo") is a Python library containing state-of-the-art algorithms for performing multivariate hypothesis tests. It is open-source and released under the MIT license.
Currently available in Python, Development versions in both R (github and CRAN) and MATLAB support only MGC. hyppo was formerly known as mgcpy.
Manuscript reproduction for the Discriminability paper can be found at Discriminability Reproduction.
Publications
- C. Shen, S. Panda, and J. T. Vogelstein. Learning Interpretable Characteristic Kernels via Decision Forests. arXiv, 2023.
- C. Shen, S. Panda, and J. T. Vogelstein. The Chi-Square Test of Distance Correlation. Journal of Computational and Graphical Statistics, (ja)0:1–21, 2021.
- S. Panda, S. Palaniappan, J. Xiong, E. W. Bridgeford, . Mehta, C. Shen, and J. T. Vogelstein. hyppo: A Multivariate Hypothesis Testing Python Package. arXiv, 2021.
- G. Franca, M. Rizzo, and J. T. Vogelstein. Kernel k-Groups via Hartigan's Method. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020.
- Y. Lee, C. Shen, C. E. Priebe, and J. T. Vogelstein. Network dependence testing via diffusion maps and distance-based correlations. Biometrika, 2019.
- J. T. Vogelstein, E. W. Bridgeford, Q. Wang, C. E. Priebe, M. Maggioni, and C. Shen. Discovering and deciphering relationships across disparate data modalities. eLife, 2019.
- C. Shen, C. E. Priebe, and J. T. Vogelstein. From Distance Correlation to Multiscale Graph Correlation. Journal of the American Statistical Association, 2018.
- S. Wang, C. Shen, A. Badea, C. E. Priebe, and J. T. Vogelstein. Signal Subgraph Estimation Via Vertex Screening. arXiv, 2018.