method, Singular Value Decomposition (SVD) can be thought of as more fundamental, because SVD not only provides a direct approach to calculate the principal components (PCs), but also derives the PCAs in row and column spaces simultaneously. In this paper, we view a set of curves as a two-way data matrix, explore the connections and differences between SVD and PCA from a FDA view point, and propose several visualization methods for the SVD components. Let X be a data matrix. In the statistical literature…
Words 9904 - Pages 40