2017  Buch
Dynamic Data Analysis
Modeling Data with Differential Equations
Über dieses Buch
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.
 Titel
 Dynamic Data Analysis
 Verlag

Springer New York
 Print ISBN
 9781493971886
 Electronic ISBN
 9781493971909
 CopyrightJahr
 2017
 DOI

https://doi.org/10.1007/9781493971909
 Autoren:

James Ramsay
Giles Hooker
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