Models for dependent time series /

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 statisti...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Tunnicliffe-Wilson, Granville
Otros Autores: Reale, Marco, Haywood, John (Mathematics professor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Boca Raton : Taylor & Francis, 2015.
Colección:Chapman & Hall/CRC Monographs on Statistics & Applied Probability.
Temas:
Time-series analysis.
Autoregression (Statistics)
Mathematical statistics.
Série chronologique.
Autorégression (Statistique)
Mathematical statistics
Time-series analysis
Abhängigkeit
Autoregressives Modell
Zeitreihenanalyse
Acceso en línea:Texto completo
Descripción
Sumario: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.
Notas:"A CRC title."
Descripción Física:1 online resource
Bibliografía:Includes bibliographical references and index.
ISBN:1420011502
9781420011500

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