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Functional Data Analysis (Springer Series in Statistics)

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Published by Springer .
Written in English


Book details:

The Physical Object
Number of Pages430
ID Numbers
Open LibraryOL7445776M
ISBN 10038740080X
ISBN 109780387400808

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The data sets exemplify the wide scope of functional data analysis; they are drawn from growth analysis, meteorology, biomechanics, equine science, economics, and medicine. The book presents novel statistical technology, much of it based on the authors’ own research work, while keeping the mathematical level widely accessible/5(7).   The data sets exemplify the wide scope of functional data analysis; they are drawn from growth analysis, meteorology, biomechanics, equine science, economics, and medicine. The book presents novel statistical technology, much of it based on the authors’ own research work, while keeping the mathematical level widely accessible.5/5(1). The data sets exemplify the wide scope of functional data analysis; they are drwan from growth analysis, meterology, biomechanics, equine science, economics, and medicine. The book presents novel statistical technology while keeping the mathematical level widely accessible. Anuj Srivastava is a Professor in the Department of Statistics and a Distinguished Research Professor at Florida State University. His areas of interest include statistical analysis on nonlinear manifolds, statistical computer vision, functional data analysis, and statistical shape theory.

The data sets exemplify the wide scope of functional data analysis; they are drwan from growth analysis, meterology, biomechanics, equine science, economics, and medicine. The book presents novel statistical technology while keeping the mathematical level widely accessible. It is designed to appeal to students, to applied data analysts, and to. The data sets exemplify the wide scope of functional data analysis; they are drawn from growth analysis, meteorology, biomechanics, equine science, economics, and medicine. The book presents novel statistical technology, much of it based on the authorsÕ own research work, while keeping the mathematical level widely accessible. Functional data analysis is a new area of statistical research, and these two leading figures present the first collection of methods in book-form. Much of . Introduction to Functional Data Analysis provides a concise textbook introduction to the field. It explains how to analyze functional data, both at exploratory and inferential levels. It also provides a systematic and accessible exposition of the methodology and .

Functional Data Analysis Some References Three references for this course (all Springer) Ramsay & Silverman, , Functional Data Analysis Ramsay & Silverman, , Applied Functional Data Analysis Ramsa,y Hooker & Graves, , Functional Data Analysis in R and Matlab Relevant Sofware: fda package in R 3/ General functional data analysis fda provides functions to enable all aspects of functional data analysis: It includes object-types for functional data with corresponding functions for smoothing, plotting and regression models. The package includes data sets and script files for working examples from the book: Ramsay, J. O., Hooker, Giles, and Cited by: 1.   This book contains the ideas of functional data analysis by a number of case studies. The case studies are accessible to research workers in a wide range of disciplines. Every reader should gain not only a specific understanding of the methods of functional data analysis, but more importantly a general insight into the underlying patterns of /5(5).   Functional Data Analysis book. Read reviews from world’s largest community for readers. Scientists today collect samples of curves and other functional o 4/5.