Tensor Regression for Incomplete Observations (TRIO)
Tensor Regression for Incomplete Observations (TRIO) with Application to Longitudinal Studies
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TRIO
Tensor Regression for Incomplete Observations (TRIO) with Application to Longitudinal Studies
Main Functions:
TRIO.m: This is a function to conduct TRIO regression.
TRIO_corr.m: This is an internal function to conduct TRIO with variance/covariance matrix.
test.m: To test and show examples of the TRIO functions.
Functions used in simulation:
randcorr.m, ten_mat.m: Helping functions.
simulation.m: Codes for the simulation study.
Additional folders:
tensor_toolbox-v3.4: tensor toolbox for Matlab (necessary for TRIO)
SLEP-master: Sparse Learning with Efficient Projections toolbox for Matlab (necessary for TRIO)
DISCOM: DISCOM method
CP regression: TensorReg toolbox for CP regression
Cite As
Peter Xu (2026). Tensor Regression for Incomplete Observations (TRIO) (https://github.com/zjph602xtc/TRIO/releases/tag/v1.0), GitHub. Retrieved .
General Information
- Version 1.0 (10.5 MB)
-
View License on GitHub
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
| Version | Published | Release Notes | Action |
|---|---|---|---|
| 1.0 |
