Abstract
Functional data come in many forms, but their defining quality is that they consist of functions—often, but not always, smooth curves. In this book, we consider functional data arising in many different fields, ranging from the shapes of bones excavated by archaeologists, to economic data collected over many years, to the path traced out by a juggler’s finger. The fundamental aims of the analysis of functional data are the same as those of more conventional statistics: to formulate the problem at hand in a way amenable to statistical thinking and analysis; to develop ways of presenting the data that highlight interesting and important features; to investigate variability as well as mean characteristics; to build models for the data observed, including those that allow for dependence of one observation or variable on another, and so on.
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© 2002 Springer-Verlag New York, Inc.
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(2002). Introduction. In: Ramsay, J.O., Silverman, B.W. (eds) Applied Functional Data Analysis: Methods and Case Studies. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-0-387-22465-7_1
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DOI: https://doi.org/10.1007/978-0-387-22465-7_1
Publisher Name: Springer, New York, NY
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