Description
Springer Functional Data Analysis with R and MATLAB by James Ramsay, Giles Hooker, Spencer Graves
The book provides an application-oriented overview of functional analysis, with extended and accessible presentations of key concepts such as spline basis functions, data smoothing, curve registration, functional linear models and dynamic systems_x000D__x000D__x000D_Functional data analysis is put to work in a wide a range of applications, so that new problems are likely to find close analogues in this book_x000D__x000D__x000D_The code in R and Matlab in the book has been designed to permit easy modification to adapt to new data structures and research problems_x000D_ Table of contents :- _x000D_
to Functional Data Analysis.- Essential Comparisons of the Matlab and R Languages.- How to Specify Basis Systems for Building Functions.- How to Build Functional Data Objects.- Smoothing: Computing Curves from Noisy Data.- Descriptions of Functional Data.- Exploring Variation: Functional Principal and Canonical Components Analysis.- Registration: Aligning Features for Samples of Curves.- Functional Linear Models for Scalar Responses.- Linear Models for Functional Responses.- Functional Models and Dynamics._x000D_