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A Decomposition-based Canonical Correlation Analysis for High-dimensional Datasets (JASA-19 paper)
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README.md
Y_1.txt
Y_2.txt
dcca.py
example.py

README.md

D-CCA

This python package implements the D-CCA method proposed in [1]. See example.py for details, with Python 3.5 or above.

D-CCA conducts the following decomposition:

Y_k =  X_k + E_k = C_k + D_k + E_k   for   k=1,2

where C_1 and C_2 share the same latent factors, but D_1 and D_2 have uncorrelated latent factors.

Please cite the article [1] for this package, which is available here.

[1] Hai Shu, Xiao Wang & Hongtu Zhu (2018) D-CCA: A Decomposition-based Canonical Correlation Analysis for High-dimensional Datasets, Journal of the American Statistical Association, DOI: 10.1080/01621459.2018.1543599

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