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James Ramsay

Dynamic Data Analysis

Modeling Data with Differential Equations

Ebook (PDF Format)

This text focuses on the use of smoothing methods for developing and estimating differential equations following recent developments in functional data analysis and building on techniques described in Ramsay and Silverman (2005) Functional Data Analysis. The central concept of a dynamical system as a buffer that translates sudden changes in input into smooth controlled output responses has led to applications of previously analyzed data, opening up entirely new opportunities for dynamical systems. The technical level has been kept low so that those with little or no exposure to differential equations as modeling objects can be brought into th… Mehr

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Produktdetails


Weitere Autoren: Hooker, Giles
  • ISBN: 978-1-4939-7190-9
  • EAN: 9781493971909
  • Produktnummer: 23652596
  • Verlag: Springer-Verlag GmbH
  • Sprache: Englisch
  • Erscheinungsjahr: 2017
  • Seitenangabe: 230 S.
  • Plattform: PDF
  • Masse: 6'530 KB
  • Auflage: 1st ed. 2017
  • Abbildungen: 34 schwarz-weiße und 50 farbige Abbildungen, 53 farbige Tabellen, Bibliographie

Über den Autor


Jim Ramsay, PhD, is Professor Emeritus of Psychology and an Associate Member in the Department of Mathematics and Statistics at McGill University. He received his PhD from Princeton University in 1966 in quantitative psychology. He has been President of the Psychometric Society and the Statistical Society of Canada. He received the Gold Medal in 1998 for his contributions to psychometrics and functional data analysis and Honorary Membership in 2012 from the Statistical Society of Canada. Giles Hooker, PhD, is Associate Professor of Biological Statistics and Computational Biology at Cornell University. In addition to differential equation models, he has published extensively on functional data analysis and uncertainty quantification in machine learning. Much of his methodological work is inspired by collaborations in ecology and citizen science data.

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