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Principal differential analysis with a continuous covariate: low-dimensional approximations for functional data
Given a collection of n curves that are independent realizations of a functional variable, we are interested in finding patterns in the curve data by exploring low dimensional approximations to the curves. It is assumed that the data curves are noisy samples from the vector space span{f1, …, fm }, …