Smoothed Functional Data Analysis

Abstract


As science develops, data in the form of functions (rather than numbers or vectors) are being collected more frequently in fields such as biology and the medical sciences, among others. Of interest is how to deal with such data. In this presentation, an overview of functional data analysis is given. Methodologies for functional hypothesis testing and automatic choice of dimensionality of principal components are proposed and studied. Real data applications and simulation studies show the usefulness of these new approaches.

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