Select the optimal order of latent variables for PCA/ICA/PPCA/PICA/CCA. This is a public version of the original repository selectOrder, which is private. I've added simple demos that use the functions. Please feel free to contact me for help on getting started. I'm happy to help.

This tool-box contains order selection algorithms for linear admixture models (see this link). Most existing methods are based on information-theoretic criteria, see this document and typically use the log-likelihood fucntion. The proposed algorithm used here is not based on the relatively complex likelihood function, and therefore has been shown to produce more consistent results.

Please make sure to cite the our paper:

This repository contains code for two types of algorithms:

• single-vector factor analysis models (e.g., PCA) Python and Matlab
• double-vector analysis (e.g., CCA) Matlab

• numpy, scipy

Additionally, for experiments on real FMRI data:

• nipype (This automatically installs some pre-req modules, e.g., nibabel)
• nilearn

Note: Installing nipype on Windows Anaconda is a bit tricky. This is because pip isn't able to directly install traits. The solution for me was to download the traits wheel from from here and then run

pip install <location of trait wheel file>.whl

• Matlab version at the time of publishing this code was 2017b

For direction-of-arrival simulations in the CCA directory, I use doa-tools. You can find a forked version here in case @morriswmz changes the original.

Thanks for showing interest. For more code/projects, please visit my page.

NS, 2018