Time series analysis / Henrik Madsen.

By: Madsen, HenrikMaterial type: TextTextSeries: Chapman & Hall/CRC texts in statistical science series ; 72.Publication details: Boca Raton : Chapman & Hall/CRC, 2008. Description: 380 p. : il. ; 25 cmISBN: 978-1-4200-5967-0 (hbk); 1-4200-5967-X (hbk)Subject(s): Series estadísticas | Análisis de series temporalesSummary: 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.
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Item type Home library Call number URL Status Date due Barcode Item holds
Fuera de préstamo 07. BIBLIOTECA CIENCIAS SOCIALES Y JURÍDICAS
519.24/MAD/tim*Prof. D. Coronado (Browse shelf(Opens below)) Texto completo Not for loan 3742497164
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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.

Bibliografía: (p. [367]-372). - Indice.

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