Functional Principal Component Analysis

Introduction Functional Principal Component Analysis (FPCA) is a generalization of PCA where entire functions act as samples ($latex X in L^2(mathcal{T})&bg=ffffff$ over time a interval $latex mathcal{T}&bg=ffffff$) instead of scalar values ($latex X in mathbb{R}^p&bg=ffffff$). The FPCA can be used to find the dominant modes of a set of functions. One of the central ideas … Continue reading Functional Principal Component Analysis