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Models for dependent time series / / Granville Tunnicliffe-Wilson, Department of Mathematics and Statistics, Lancaster University, UK; Marco Reale, School of Mathematics and Statistics, University of Canterbury, New Zealand; John Haywood, School of Mathematics and Statistics, Victoria University of Wellington, New Zealand



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Autore: Tunnicliffe-Wilson Granville Visualizza persona
Titolo: Models for dependent time series / / Granville Tunnicliffe-Wilson, Department of Mathematics and Statistics, Lancaster University, UK; Marco Reale, School of Mathematics and Statistics, University of Canterbury, New Zealand; John Haywood, School of Mathematics and Statistics, Victoria University of Wellington, New Zealand Visualizza cluster
Pubblicazione: Boca Raton : , : CRC Press, , 2015
Descrizione fisica: 1 online resource (320 p.)
Disciplina: 519.5/5
519.55
Soggetto topico: Time-series analysis
Autoregression (Statistics)
Mathematical statistics
Persona (resp. second.): RealeMarco
HaywoodJohn (Mathematics professor)
Note generali: A Chapman & Hall book.
Nota di bibliografia: Includes bibliographical references.
Nota di contenuto: ""Cover""; ""Contents""; ""Preface""; ""Chapter 1: Introduction and overview""; ""Chapter 2: Lagged regression and autoregressive models""; ""Chapter 3: Spectral analysis of dependent series""; ""Chapter 4: Estimation of vector autoregressions""; ""Chapter 5: Graphical modeling of structural VARs""; ""Chapter 6: VZAR: An extension of the VAR model""; ""Chapter 7: Continuous time VZAR models""; ""Chapter 8: Irregularly sampled series""; ""Chapter 9: Linking graphical, spectral and VZAR methods""; ""References""
Sommario/riassunto: Models for Dependent Time Series addresses the issues that arise and the methodology that can be applied when the dependence between time series is described and modeled. Whether you work in the economic, physical, or life sciences, the book shows you how to draw meaningful, applicable, and statistically valid conclusions from multivariate (or vector) time series data.The first four chapters discuss the two main pillars of the subject that have been developed over the last 60 years: vector autoregressive modeling and multivariate spectral analysis. These chapters provide the foundational mater
Titolo autorizzato: Models for dependent time series  Visualizza cluster
ISBN: 0-429-14440-7
1-4200-1150-2
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910797359503321
Lo trovi qui: Univ. Federico II
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Serie: Monographs on statistics and applied probability (Series) ; ; Volume 142.