R package msda: Multi-Class Sparse Discriminant Analysis. Efficient procedures for computing a new Multi-Class Sparse Discriminant Analysis method that estimates all discriminant directions simultaneously.
Keywords for this software
References in zbMATH (referenced in 11 articles , 1 standard article )
Showing results 1 to 11 of 11.
- Jiang, Binyan; Chen, Ziqi; Leng, Chenlei: Dynamic linear discriminant analysis in high dimensional space (2020)
- Luo, Shan; Chen, Zehua: A procedure of linear discrimination analysis with detected sparsity structure for high-dimensional multi-class classification (2020)
- Oda, Ryoya; Suzuki, Yuya; Yanagihara, Hirokazu; Fujikoshi, Yasunori: A consistent variable selection method in high-dimensional canonical discriminant analysis (2020)
- Pan, Yuqing; Mai, Qing: Efficient computation for differential network analysis with applications to quadratic discriminant analysis (2020)
- Yu, Weichang; Ormerod, John T.; Stewart, Michael: Variational discriminant analysis with variable selection (2020)
- Liu, Jianyu; Yu, Guan; Liu, Yufeng: Graph-based sparse linear discriminant analysis for high-dimensional classification (2019)
- Mai, Qing; Yang, Yi; Zou, Hui: Multiclass sparse discriminant analysis (2019)
- Pan, Yuqing; Mai, Qing; Zhang, Xin: Covariate-adjusted tensor classification in high dimensions (2019)
- Sheng, Ying; Wang, Qihua: Simultaneous variable selection and class fusion with penalized distance criterion based classifiers (2019)
- Jiang, Binyan; Wang, Xiangyu; Leng, Chenlei: A direct approach for sparse quadratic discriminant analysis (2018)
- Karl Sjöstrand; Line Clemmensen; Rasmus Larsen; Gudmundur Einarsson; Bjarne Ersbøll: SpaSM: A MATLAB Toolbox for Sparse Statistical Modeling (2018) not zbMATH