Isbn: 9781493984121 - dynamic data analysis: modeling data with differential equations (11 risultati)

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  • Lingua: Inglese

    Editore: Springer, 2018

    1493984128 / 9781493984121

    Serie: Libro 146 di 160 - Springer Series in Statistics

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    Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections

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    Condizione: New. In English.

  • Lingua: Inglese

    Editore: Springer, 2018

    1493984128 / 9781493984121

    Serie: Libro 146 di 160 - Springer Series in Statistics

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    Condizione: New. Softcover reprint of the original 1st ed. 2017 edition NO-PA16APR2015-KAP.

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    Lingua: Inglese

    Editore: Springer, 2018

    1493984128 / 9781493984121

    Serie: Libro 146 di 160 - Springer Series in Statistics

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    Taschenbuch. Condizione: Neu. Dynamic Data Analysis | Modeling Data with Differential Equations | James Ramsay (u. a.) | Taschenbuch | Springer Series in Statistics | xvii | Englisch | 2018 | Springer | EAN 9781493984121 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

  • Lingua: Inglese

    Editore: Springer, 2018

    1493984128 / 9781493984121

    Serie: Libro 146 di 160 - Springer Series in Statistics

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    Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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    Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 this data analysis landscape. There are already many texts on the mathematical properties of ordinary differential equations, or dynamic models, and there is a large literature distributed over many fields on models for real world processes consisting of differential equations. However, a researcher interested in fitting such a model to data, or a statistician interested in the properties of differential equations estimated from data will find rather less to work with. This book fills that gap.

  • Lingua: Inglese

    Editore: Springer, 2018

    1493984128 / 9781493984121

    Serie: Libro 146 di 160 - Springer Series in Statistics

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    Da: Mispah books, Redhill, SURRE, Regno UnitoMispah books

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    Paperback. Condizione: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

  • Lingua: Inglese

    Editore: Springer, 2018

    1493984128 / 9781493984121

    Serie: Libro 146 di 160 - Springer Series in Statistics

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    Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand

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    Condizione: new. Questo è un articolo print on demand.

  • Lingua: Inglese

    Editore: Springer New York Jul 2018, 2018

    1493984128 / 9781493984121

    Serie: Libro 146 di 160 - Springer Series in Statistics

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    Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

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    Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 this data analysis landscape. There are already many texts on the mathematical properties of ordinary differential equations, or dynamic models, and there is a large literature distributed over many fields on models for real world processes consisting of differential equations. However, a researcher interested in fitting such a model to data, or a statistician interested in the properties of differential equations estimated from data will find rather less to work with. This book fills that gap. 248 pp. Englisch.

  • Lingua: Inglese

    Editore: Springer New York, 2018

    1493984128 / 9781493984121

    Serie: Libro 146 di 160 - Springer Series in Statistics

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    Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Offers&nbspan accessible text to&nbspthose with little or no exposure to differential equations as modeling objects&nbspUpdates and builds on techniques from the popular Functional Data Analysis (Ramsay and Silverman, 2005)Opens u.

  • Lingua: Inglese

    Editore: Springer, 2018

    1493984128 / 9781493984121

    Serie: Libro 146 di 160 - Springer Series in Statistics

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    Da: Majestic Books, Hounslow, Regno UnitoMajestic Books

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  • Lingua: Inglese

    Editore: Springer, Springer US Jul 2018, 2018

    1493984128 / 9781493984121

    Serie: Libro 146 di 160 - Springer Series in Statistics

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    Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000

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    Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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 this data analysis landscape. There are already many texts on the mathematical properties of ordinary differential equations, or dynamic models, and there is a large literature distributed over many fields on models for real world processes consisting of differential equations. However, a researcher interested in fitting such a model to data, or a statistician interested in the properties of differential equations estimated from data will find rather less to work with. This book fills that gap.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 248 pp. Englisch.

  • Lingua: Inglese

    Editore: Springer, 2018

    1493984128 / 9781493984121

    Serie: Libro 146 di 160 - Springer Series in Statistics

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    Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios

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