Abstract
So far in this book, we have concentrated on analysing the variability of a single functional variable, albeit one that may have a rather complicated structure. In classical statistics, techniques such as linear regression, the analysis of variance, and the general linear model all approach the question of how variation in an observed variable may be accounted for by other observed quantities. We now extend these general ideas to the functional context.
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© 1997 Springer Science+Business Media New York
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Ramsay, J.O., Silverman, B.W. (1997). Functional linear models. In: Functional Data Analysis. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4757-7107-7_9
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DOI: https://doi.org/10.1007/978-1-4757-7107-7_9
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4757-7109-1
Online ISBN: 978-1-4757-7107-7
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