A fast and efficient spectra standardization algorithm named principal components canonical correlation analysis (PC-CCA) has been proposed. Compared with commonly used method like PDS and CTCCA, the PC-CCA can reduce prediction errors and achieve the best RMSEPs. PC-CCA can also drastically reduce time of transfer and lead to hundreds-fold speedup. The programming language is Python.
Python 3.5 is recommended
1.Numpy
pip install numpy
2.Scipy
pip install Scipy
3.Matplotlib
pip install Matplotlib
git clone https://github.com/xiaqiong/PC-CCA.git
Zhi-Min Zhang: zmzhang@csu.edu.cn