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Time Series Analysis Methods and Applications [Hardcover]

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  • Category: Books (Mathematics)
  • ISBN-10:  0444538585
  • ISBN-10:  0444538585
  • ISBN-13:  9780444538581
  • ISBN-13:  9780444538581
  • Publisher:  North Holland
  • Publisher:  North Holland
  • Pages:  776
  • Pages:  776
  • Binding:  Hardcover
  • Binding:  Hardcover
  • Pub Date:  01-Jun-2012
  • Pub Date:  01-Jun-2012
  • SKU:  0444538585-11-MPOD
  • SKU:  0444538585-11-MPOD
  • Item ID: 100926960
  • Seller: ShopSpell
  • Ships in: 2 business days
  • Transit time: Up to 5 business days
  • Delivery by: Dec 27 to Dec 29
  • Notes: Brand New Book. Order Now.

The field of statistics not only affects all areas of scientific activity, but also many other matters such as public policy. It is branching rapidly into so many different subjects that a series of handbooks is the only way of comprehensively presenting the various aspects of statistical methodology, applications, and recent developments. The Handbook of Statistics is a series of self-contained reference books. Each volume is devoted to a particular topic in statistics, with Volume 30 dealing with time series. The series is addressed to the entire community of statisticians and scientists in various disciplines who use statistical methodology in their work. At the same time, special emphasis is placed on applications-oriented techniques, with the applied statistician in mind as the primary audience.



  • Comprehensively presents the various aspects of statistical methodology
  • Discusses a wide variety of diverse applications and recent developments
  • Contributors are internationally renowened experts in their respective areas
1. Bootstrap methods for time series
2. Testing time series linearity: traditional and bootstrap methods
3. The quest for nonlinearity in Time Series
4. Modelling nonlinear and nonstationary time series,
5. Markov switching time series models
6. A review of robust estimation under conditional heteroscedasticity
7. Functional time series
8. Covariance matrix estimation in Time Series
9. Time series quantile regressions
10. Frequency domain techniques in the analysis of DNA sequences
11. Spatial time series modelling for fMRI data analysis in neurosciences
12. Count time series models
13. Locally stationary processes
14. Analysis of multivariate non-stationary time series using the localised Fourier Liblƒ9
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