Viser: Time Series Analysis

Time Series Analysis, 1. udgave
Søgbar e-bog

Time Series Analysis Vital Source e-bog

Henrik Madsen
(2007)
CRC Press
1.328,00 kr.
Leveres umiddelbart efter køb
Time Series Analysis

Time Series Analysis

Henrik Madsen
(2005)
Sprog: Engelsk
CRC Press LLC
599,00 kr.
Flere end 10 stk på lager
Hvor kan jeg afhente varen?
Print on demand. Leveringstid vil være ca 2-3 uger.

Detaljer om varen

  • 1. Udgave
  • Vital Source searchable e-book (Fixed pages)
  • Udgiver: CRC Press (November 2007)
  • ISBN: 9781420059687
With a focus on analyzing and modeling linear dynamic systems using statistical methods, Time Series Analysis formulates various linear models, discusses their theoretical characteristics, and explores the connections among stochastic dynamic models. Emphasizing the time domain description, the author presents theorems to highlight the most
Licens varighed:
Bookshelf online: 5 år fra købsdato.
Bookshelf appen: ubegrænset dage fra købsdato.

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Print: 2 sider kan printes ad gangen
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Detaljer om varen

  • Hardback: 400 sider
  • Udgiver: CRC Press LLC (August 2005)
  • ISBN: 9781420059670
With a focus on analyzing and modeling linear dynamic systems using statistical methods, Time Series Analysis formulates various linear models, discusses their theoretical characteristics, and explores the connections among stochastic dynamic models.

Emphasizing the time domain description, the author presents theorems to highlight the most important results, proofs to clarify some results, and problems to illustrate the use of the results for modeling real-life phenomena.

The book first provides the formulas and methods needed to adapt a second-order approach for characterizing random variables as well as introduces regression methods and models, including the general linear model. It subsequently covers linear dynamic deterministic systems, stochastic processes, time domain methods where the autocorrelation function is key to identification, spectral analysis, transfer-function models, and the multivariate linear process.

The text also describes state space models and recursive and adaptive methods. The final chapter examines a host of practical problems, including the predictions of wind power production and the consumption of medicine, a scheduling system for oil delivery, and the adaptive modeling of interest rates.

Concentrating on the linear aspect of this subject, Time Series Analysis provides an accessible yet thorough introduction to the methods for modeling linear stochastic systems. It will help you understand the relationship between linear dynamic systems and linear stochastic processes.

Preface. Introduction. Multivariate Random Variables. Regression-Based Methods. Linear Dynamic Systems. Stochastic Processes. Identification, Estimation, and Model Checking. Spectral Analysis. Linear Systems and Stochastic Processes. Multivariate Time Series. State Space Models of Dynamic Systems. Recursive Estimation. Real Life Inspired Problems. Appendices. Bibliography. Index.

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