Abstract
Wavelet-based functional data analysis (FDA) is a modern approach to dealing with statistical inference when observations are curves or images. Making inference (estimation and testing) in the wavelet domain is beneficial in several respects such as: reduction of dimensionality, decorrelation, localization, and regularization. This chapter gives an overview of theory for wavelet-based functional analysis, reviews relevant references, and provides some examples that will be used in the next chapters.
As can be seen even by this limited number of examples proteins carry out amazingly diverse functions.
Michael Behe
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Morettin, P.A., Pinheiro, A., Vidakovic, B. (2017). Introduction: Examples of Functional Data. In: Wavelets in Functional Data Analysis. SpringerBriefs in Mathematics. Springer, Cham. https://doi.org/10.1007/978-3-319-59623-5_1
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DOI: https://doi.org/10.1007/978-3-319-59623-5_1
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