TULIP: A Toolbox for Linear Discriminant Analysis with Penalties

Integrates several popular high-dimensional methods based on Linear Discriminant Analysis (LDA) and provides a comprehensive and user-friendly toolbox for linear, semi-parametric and tensor-variate classification as mentioned in Yuqing Pan, Qing Mai and Xin Zhang (2019) <arXiv:1904.03469>. Functions are included for covariate adjustment, model fitting, cross validation and prediction.

Version: 1.0
Depends: R (≥ 3.1.1)
Imports: tensr, Matrix, MASS, glmnet, methods
Published: 2019-04-09
Author: Yuqing Pan, Qing Mai, Xin Zhang
Maintainer: Yuqing Pan <yuqing.pan at stat.fsu.edu>
License: GPL-2
NeedsCompilation: yes
CRAN checks: TULIP results

Downloads:

Reference manual: TULIP.pdf
Package source: TULIP_1.0.tar.gz
Windows binaries: r-devel: TULIP_1.0.zip, r-devel-gcc8: TULIP_1.0.zip, r-release: TULIP_1.0.zip, r-oldrel: TULIP_1.0.zip
OS X binaries: r-release: TULIP_1.0.tgz, r-oldrel: TULIP_1.0.tgz

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