Han, Fang; Liu, Han - In: Journal of the American Statistical Association 109 (2014) 505, pp. 275-287
We propose a semiparametric method for conducting scale-invariant sparse principal component analysis (PCA) on high-dimensional non-Gaussian data. Compared with sparse PCA, our method has a weaker modeling assumption and is more robust to possible data contamination. Theoretically, the proposed...