Journal of the American Statistical Association a Generalized Least Squares Matrix Decomposition a Generalized Least Squares Matrix Decomposition Accepted Manuscript Accepted Manuscript

This work proposes a generalization of principal components analysis (PCA) that is appropriate for massive data sets with structured variables or known two-way dependencies, and develops fast computational algorithms using these methods to perform generalized PCA, sparse GPCA, and functional GPCA on massive data sets.