Multivariate time series analysis and applications/ William W.S.Wei
Series: Wiley Series in Probability and StatisticsPublication details: New Jersey: Wiley, 2019Description: xviii,518 pages, 25 cmISBN:- 978119502852
- 23 000SA.3 W415
Item type | Current library | Call number | Status | Date due | Barcode | Item holds | |
---|---|---|---|---|---|---|---|
Books | ISI Library, Kolkata | 000SA.3 W415 (Browse shelf(Opens below)) | Available | 138503 |
This book is accompanied by a companion website - www.wiley.com/go/wei/datasets
Preface -- About the companion website -- 1. Fundamental concepts and issues in multivariate time series analysis -- 2. Vector time series models -- 3. Multivariate time series regression models -- 4. Principle component analysis of multivariate time series -- 5. Factor analysis of multivariate time series -- 6. Multivariate GARCH models -- 7. Repeated measurements -- Space-time series models -- 9. Multivariate spectral analysis of time series -- 10. Dimension reduction in high-dimensional multivariate time series analysis -- Software code -- Projects
This book focuses on high dimensional multivariate time series, and is illustrated with numerous high dimensional empirical time series. Beginning with the fundamentalconcepts and issues of multivariate time series analysis,this book covers many topics that are not found in general multivariate time series books. Some of these are repeated measurements, space-time series modelling, and dimension reduction. The book also looks at vector time series models, multivariate time series regression models, and principle component analysis of multivariate time series. Additionally, it provides readers with information on factor analysis of multivariate time series, multivariate GARCH models, and multivariate spectral analysis of time series.
With the development of computers and the internet, we have increased potential for data exploration. In the next few years, dimension will become a more serious problem. Multivariate Time Series Analysis and its Applications provides some initial solutions, which may encourage the development of related software needed for the high dimensional multivariate time series analysis.
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