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Functional Data Analysis

Sofort lieferbar | Lieferzeit: Sofort lieferbar I
B.  W. Silverman
Springer Texts in Statistics Springer Series in Statistics
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"Scientists and others today often collect samples of curves and other functional observations. This monograph presents many ideas and techniques for such data. Included are expressions in the functional domain of such classics as linear regression, principal components analysis, linear modeling, and canonical correlation analysis, as well as specifically functional techniques such as curve registration and principal differential analysis. Data arising in real applications are used throughout for both motivation and illustration, showing how functional approaches allow us to see new things, especially by exploiting the smoothness of the processes generating the data. The data sets exemplify the wide scope of functional data analysis; they are drawn from growth analysis, meteorology, biomechanics, equine science, economics, and medicine.
Introduction * Notation and Techniques * Representing Functional Data as Smooth Functions * The Roughness Penalty Approach * The Registration and Display of Functional Data * Principal Components Analysis for Functional Data * Regularized Principal Components Analysis * Principal Components Analysis of Mixed Data * Functional Linear Models * Functional Linear Models for Scalar Responses * Functional Linear Modesl for Functional Responses * Canonical Correlation and Discriminant Analysis * Differential Operators in Functional Data Analysis * Principal Differential Analysis * More General Roughness Penalties * Some Perspectives on FDA

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