Functional data analysis de ramsay james (41 resultados)

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Paperback. Condición: Sehr gut. 224 pp. Very well preserved copy 338 Sprache: Englisch Gewicht in Gramm: 704.

Idioma: Inglés
Editorial: Springer, 2005
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Hardcover. Condición: Near Fine. 2nd Edition. Second edition. Sturdy glossy covers with slight bumping to upper right corner, pages clean and unmarked. xix, [1], 426, [2]pp.

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Paperback. Condición: New. 2009 ed.

S+ Functional Data Analysis: User's Manual for Windows
Douglas B. Clarkson/ Chris Fraley/ Charles C. Gu/ James O. Ramsay
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Condición: 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. Condición: 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…variable). 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.

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Paperback. Condición: New. 2009 ed.

Idioma: Inglés
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Condición: Gut. Zustand: Gut | Seiten: 325 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

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Condición: New. pp. 448 2nd Edition.

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Hardback. Condición: New. 2nd ed. 2005. 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 mo…deling, 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' other volume 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.
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Editorial: Springer, 2010
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Taschenbuch. Condición: 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: pre…igu.

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Hardback. Condición: New. 2nd ed. 2005. 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 mod…eling, 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' other recent volume 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.

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Taschenbuch. Condición: 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,… 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.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.

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Buch. Condición: 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, princi…pal 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.

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