Continuous Time Modeling in the Behavioral and Related Sciences
Language: English
Published by Springer International Publishing, 2019
- Softcover
- New
Seller: moluna, Greven, Germanymoluna
AbeBooks seller since July 9, 2020
Condition: New
£ 74.06
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Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This is the first and only book on continuous time modeling in the behavioral and related sciencesIntroduces Newtonian dynamics modeling by means of differential equations for behavioral and related sciencesCovers a vast range of topics.
Seller Inventory # 448671438
- Title
- Continuous Time Modeling in the Behavioral and Related Sciences
- Author
- van Montfort, Kees|Oud, Johan H.L.|Voelkle, Manuel C.
- Publisher
- Springer International Publishing
- Publication year
- 2019
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 10
- 3030084019
- ISBN 13
- 9783030084011
- Seller catalogs
- Mathematik/Naturwissenschaften/Technik/Medizin
This unique book provides an overview of continuous time modeling in the behavioral and related sciences. It argues that the use of discrete time models for processes that are in fact evolving in continuous time produces problems that make their application in practice highly questionable. One main issue is the dependence of discrete time parameter estimates on the chosen time interval, which leads to incomparability of results across different observation intervals. Continuous time modeling by means of differential equations offers a powerful approach for studying dynamic phenomena, yet the use of this approach in the behavioral and related sciences such as psychology, sociology, economics and medicine, is still rare. This is unfortunate, because in these fields often only a few discrete time (sampled) observations are available for analysis (e.g., daily, weekly, yearly, etc.). However, as emphasized by Rex Bergstrom, the pioneer of continuous-time modeling in econometrics, neitherhuman beings nor the economy cease to exist in between observations.
In 16 chapters, the book addresses a vast range of topics in continuous time modeling, from approaches that closely mimic traditional linear discrete time models to highly nonlinear state space modeling techniques. Each chapter describes the type of research questions and data that the approach is most suitable for, provides detailed statistical explanations of the models, and includes one or more applied examples. To allow readers to implement the various techniques directly, accompanying computer code is made available online. The book is intended as a reference work for students and scientists working with longitudinal data who have a Master's- or early PhD-level knowledge of statistics.
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About the Author
"About the title" may belong to another edition of this title.
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