Shen, Dan; Shen, Haipeng; Marron, J.S. - In: Journal of Multivariate Analysis 115 (2013) C, pp. 317-333
Sparse Principal Component Analysis (PCA) methods are efficient tools to reduce the dimension (or number of variables) of complex data. Sparse principal components (PCs) are easier to interpret than conventional PCs, because most loadings are zero. We study the asymptotic properties of these...