TensorReg Toolbox for Matlab

TensorReg toolbox is a collection of Matlab functions for tensor regressions.

The toolbox is developed by Hua Zhou.

Compatibility

The code is tested on Matlab R2017a, but should work on other versions of Matlab with no or little changes. Current version works on these platforms: Windows 64-bit, Linux 64-bit, and Mac (Intel 64-bit). Type computer in Matlab’s command window to determine the platform.

Dependency

TensorReg toolbox uses the Tensor Toolbox and SparseReg Toolbox. Please install the Tensor Toolbox (v2.6) and SparseReg Toolbox before installing the TensorReg toolbox.

Installation (Matlab version >= 2014b)

Download the Matlab toolbox installation file TensorReg.mltbx. Double click the downloaded file and you should be good to go. If it does not work for some reasons, follow the below instructions for Matlab version < 2014b.

Installation (Matlab version < 2014b)

1. Download ZIP File file using the links on the left.
2. Extract the zip file.

   unzip Hua-Zhou-TensorReg-xxxxxxx.zip
   

3. Rename the folder from Hua-Zhou-SparseReg-xxxxxxx to SparseReg.

   mv Hua-Zhou-TensorReg-xxxxxxx TensorReg
   

4. Add the TensorReg folder to Matlab search path. Start Matlab, cd to the TensorReg directory, and execute the following commands
   addpath(pwd) %<-- Add the toolbox to the Matlab path
save path %<-- Save for future Matlab sessions
5. Go through following tutorials for the usage. For help of individual functions, type ? followed by the function name in Matlab.

Tutorial

• Resize arrays
• Kruskal (CP) regression
• Tucker regression
• Regularized matrix regression

How to cite

If you use this toolbox, please cite the software itself along with at least one publication or preprint.

• Software reference:
  H Zhou. Matlab TensorReg Toolbox Version 1.0, Available online, March 2017.
• Default article to cite for Kruskal (CP) tensor regression:
  H Zhou, L Li, and H Zhu (2013) Tensor regression with applications in neuroimaging data analysis, Journal of American Statistical Association, 108(502):540-552.
• Default article to cite for Tucker tensor regression:
  X Li, H Zhou, and L Li (2018) Tucker tensor regression and neuroimaging analysis, Statistics in Biosciences, 10(3):520-545.
• Default article to cite for regularized matrix regression:
  H Zhou and L Li. (2014) Regularized matrix regression, Journal of Royal Statistical Society Series B, 76(2):463-483.

Contacts

Hua Zhou huazhou@ucla.edu