Functional data analysis von ramsay james (14 Ergebnisse)
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Paperback. Zustand: Very Good. 2009. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.
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Paperback. Zustand: Good. No Jacket. Former library book; Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.
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Weitere Bilder- Softcover
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Paperback. Zustand: Sehr gut. 224 pp. Very well preserved copy 338 Sprache: Englisch Gewicht in Gramm: 704.
S+ Functional Data Analysis: User's Manual for Windows
Douglas B. Clarkson/ Chris Fraley/ Charles C. Gu/ James O. Ramsay
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Paperback. Zustand: Brand New. 1st edition. 192 pages. 9.00x6.75x0.50 inches. In Stock.
- Softcover
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Zustand: New. Provides documentation for the S-PLUS module on functional data analysisWill supplement our two books on this topic by Ramsay/SilvermanThis book can be considered a companion to two other highly acclaimed books involving James Ramsay an.
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - S+Functional Data Analysis is the first commercial object oriented package for exploring, modeling, and analyzing functional data. Functional data analysis (FDA) handles longitudinal data and treats each observation as a function of time (or other va…riable). The functions are related. The goal is to analyze a sample of functions instead of a sample of related points. FDA differs from traditional data analytic techniques in a number of ways. Functions can be evaluated at any point in their domain. Derivatives and integrals, which may provide better information (e.g. graphical) than the original data, are easily computed and used in multivariate and other functional analytic methods.The analyst using S+FDA can handle irregularly spaced data or data with missing values. For large amounts of data, working with a functional representation can save storage. Moreover, S+FDA provides a variety of analytic techniques for functional data including linear models, generalized linear models, principal components, canonical correlation, principal differential analysis, and clustering.This book can be considered a companion to two other highly acclaimed books involving James Ramsay and Bernard Silverman: Functional Data Analysis, Second Edition (2005) and Applied Functional Data Analysis (2002). This user's manual also provides the documentation for the S+FDA library for SPlus.From the reviews:'The book offers an overview of the basics of functional data approaches as well as a weath of information, sample code, and examples about each of these methods in a clear well-presented manner. The book provides a well-written discussion of how and when to use the functions, and it will be a useful and convenient reference for those getting started with functional analyses.' The American Statistician, May 2006, Vol. 60, No. 2.
Sprache: Englisch
Verlag: SPRINGER VERLAG GMBH + CO, 1997
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Zustand: Gut. Zustand: Gut | Seiten: 325 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.
Sprache: Englisch
Verlag: Springer, 2005
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Sprache: Englisch
Verlag: Springer, 2010
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Weitere BilderSprache: Englisch
Verlag: Springer, 2010
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Taschenbuch. Zustand: Neu. Functional Data Analysis | James Ramsay (u. a.) | Taschenbuch | Springer Series in Statistics | xix | Englisch | 2010 | Springer | EAN 9781441923004 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preig…u.
Sprache: Englisch
Verlag: Springer, Humana, 2010
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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, p…rincipal 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.The book presents novel statistical technology, much of it based on the authors' own research work, 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. This second edition is aimed at a wider range of readers, and especially those who would like to apply these techniques to their research problems.It complements the authors' othervolume Applied Functional Data Analysis: Methods and Case Studies. In particular, there is an extended coverage of data smoothing and other matters arising in the preliminaries to a functional data analysis.The chapters on the functional linear model and modeling of the dynamics of systems through the use of differential equations and principal differential analysis have been completely rewritten and extended to include new developments.Other chapters have been revised substantially, often to give more weight to examples and practical considerations.
Sprache: Englisch
Verlag: Springer, Humana, 2005
- Hardcover
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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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, principa…l 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.The book presents novel statistical technology, much of it based on the authors' own research work, 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. This second edition is aimed at a wider range of readers, and especially those who would like to apply these techniques to their research problems.It complements the authors' othervolume Applied Functional Data Analysis: Methods and Case Studies. In particular, there is an extended coverage of data smoothing and other matters arising in the preliminaries to a functional data analysis.The chapters on the functional linear model and modeling of the dynamics of systems through the use of differential equations and principal differential analysis have been completely rewritten and extended to include new developments.Other chapters have been revised substantially, often to give more weight to examples and practical considerations.
