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Performs classification and variable selection on high-dimensional tensors (multi-dimensional arrays) after adjusting for additional covariates (scalar or vectors) as CATCH model in Pan, Mai and Zhang (2018) <doi:10.48550/arXiv.1805.04421>. The low-dimensional covariates and the high-dimensional tensors are jointly modeled to predict a categorical outcome in a multi-class discriminant analysis setting. The Covariate-Adjusted Tensor Classification in High-dimensions (CATCH) model is fitted in two steps: (1) adjust for the covariates within each class; and (2) penalized estimation with the adjusted tensor using a cyclic block coordinate descent algorithm. The package can provide a solution path for tuning parameter in the penalized estimation step. Special case of the CATCH model includes linear discriminant analysis model and matrix (or tensor) discriminant analysis without covariates.
| Version: | 1.0.1 |
| Depends: | R (≥ 3.1.1) |
| Imports: | tensr, Matrix, MASS, methods |
| Published: | 2021-01-04 |
| Author: | Yuqing Pan, Qing Mai, Xin Zhang |
| Maintainer: | Yuqing Pan <yuqing.pan at stat.fsu.edu> |
| License: | GPL-2 |
| NeedsCompilation: | yes |
| CRAN checks: | catch results |
| Reference manual: | catch.pdf |
| Package source: | catch_1.0.1.tar.gz |
| Windows binaries: | r-devel: catch_1.0.1.zip, r-release: catch_1.0.1.zip, r-oldrel: catch_1.0.1.zip |
| macOS binaries: | r-release (arm64): catch_1.0.1.tgz, r-oldrel (arm64): catch_1.0.1.tgz, r-release (x86_64): catch_1.0.1.tgz, r-oldrel (x86_64): catch_1.0.1.tgz |
| Old sources: | catch archive |
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