Package: catch
Title: Covariate-Adjusted Tensor Classification in High-Dimensions
Version: 1.0.1
Description: 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) <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.
Depends: R (>= 3.1.1)
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: tensr, Matrix, MASS, methods
NeedsCompilation: yes
Packaged: 2021-01-04 11:46:44 UTC; ypan
Author: Yuqing Pan <yuqing.pan@stat.fsu.edu>,
	Qing Mai <mai@stat.fsu.edu>,
	Xin Zhang <henry@stat.fsu.edu>
Maintainer: Yuqing Pan <yuqing.pan@stat.fsu.edu>
Repository: CRAN
Date/Publication: 2021-01-04 17:10:02 UTC
Built: R 4.6.0; x86_64-apple-darwin20; 2026-04-27 07:55:18 UTC; unix
Archs: catch.so.dSYM
