×

Uh-oh, it looks like your Internet Explorer is out of date.

For a better shopping experience, please upgrade now.

Handbook of Statistics: Time Series Analysis: Methods and Applications
     

Handbook of Statistics: Time Series Analysis: Methods and Applications

by Elsevier Science
 

See All Formats & Editions

ISBN-10: 0444538585

ISBN-13: 9780444538581

Pub. Date: 07/27/2012

Publisher: Elsevier Science

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

Overview

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

Product Details

ISBN-13:
9780444538581
Publisher:
Elsevier Science
Publication date:
07/27/2012
Series:
Handbook of Statistics Series , #30
Pages:
774
Product dimensions:
6.20(w) x 9.10(h) x 1.40(d)

Table of Contents

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 Library
15. An alternative perspective on stochastic coefficient regression models
16. Hierarachical Bayesian models for space-time air pollution data
17. Karhunen-Loeve expansion for temporal and spatio-temporal processes
18. Statistical analysis of spatio-temporal models and their applications
19. Lévy-driven time series models for financial data
20. Discrete and continuous time extremes of stationary processesn
21. The estimation of Frequency
22. A wavelet variance primer
23. Time Series Analysis with R

Customer Reviews

Average Review:

Post to your social network

     

Most Helpful Customer Reviews

See all customer reviews