Functional data analysis
J. O. Ramsay
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Functional data analysis
by J. O. Ramsay
Published
2006
Publisher
Springer
Pages
426
ISBN-13
9781601193094
ISBN-10
1601193092
Description
Scientists today 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 modelling, 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 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 experienced researchers; it will have value both within statistics and across a broad spectrum of other fields. Much of the material is based on the authors' own work, some of which appears here for the first time. Jim Ramsay is Professor of Psychology at McGill University and is an international authority on many aspects of multivariate analysis. He draws on his collaboration with researchers in speech articulation, motor control, meteorology, psychology, and human physiology to illustrate his technical contributions to functional data analysis in a wide range of statistical and application journals. Bernard Silverman, author of the highly regarded "Density Estimation for Statistics and Data Analysis," and coauthor of "Nonparametric Regression and Generalized Linear Models: A Roughness Penalty Approach," is Professor of Statistics at Bristol University. His published work on smoothing methods and other aspects of applied, computational, and theoretical statistics has been recognized by the Presidents' Award of the Committee of Presidents of Statistical Societies, and the award of two Guy Medals by the Royal Statistical Society.
Multivariate data analysis
Statistical analysis for decision making
Multivariate statistical methods
Theory and application of the linear model
Using multivariate statistics
Applied regression analysis and other multivariable methods
Frequently Asked Questions
How many pages are in Functional data analysis?
This edition of Functional data analysis has approximately 426 pages. Please note, this is an estimate and the exact page count can vary between hardcover, paperback, and e-book versions.
How long does it take to read Functional data analysis?
For most readers, Functional data analysis typically takes between 8h 53m and 5h 55m to complete. This is based on the book's length of approximately 106,500 words and common reading speeds.
Here's a detailed breakdown: • Continuous reading at 250 WPM: approximately 7h 6m of focused reading • Casual reading (30 minutes/day): you could finish in roughly 15 days • Estimated word count: 106,500 words
Your individual reading time will vary based on your personal reading pace, the amount of daily reading time, and your familiarity with the subject matter.
What is the word count of Functional data analysis?
The estimated word count for Functional data analysis is approximately 106,500 words. This figure is calculated using industry-standard methods that consider genre-specific word density patterns, typical formatting and layout characteristics, and standard words-per-page ratios for published books.
This is an approximation — actual word count may vary based on font size, formatting, edition, and the presence of illustrations or charts.
Who is the author of Functional data analysis?
Functional data analysis was written by J. O. Ramsay.
When was Functional data analysis published?
The publication date for this specific edition is 2006. The original work may have been published on a different date.