2 papers
stat.ME2025
Beyond Regularization: Inherently Sparse Principal Component Analysis
Jan O. Bauer
Sparse principal component analysis (sparse PCA) is a widely used technique for dimensionality reduction in multivariate analysis, addressing two key limitations of standard PCA. F…
stat.ME2025
Localized Functional Principal Component Analysis Based on Covariance Structure
Maria Laura Battagliola, Jan O. Bauer
Functional principal component analysis (FPCA) is a widely used technique in functional data analysis for identifying the primary sources of variation in a sample of random curves.…