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.
||R (≥ 3.1.1)
||tensr, Matrix, MASS, glmnet, methods
||Yuqing Pan <yuqing.pan at stat.fsu.edu>
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