Part 1 Bootstrap and tests for linearity of a time series
1. Bootstrap methods for time series, J-P. Kreiss and S. Lahiri.
2. Testing time series linearity: traditional and bootstrap methods, A. Berg, T. McMurry
and D. N. Politis
3. The quest for nonlinearity in Time Series, S. Giannerini
Part II Nonlinear time series
4. Modelling nonlinear and nonstationary time series, D. Tjøstheim
5. Markov switching time series models, J. Franke
6. A review of robust estimation under conditional heteroscedasticity, K. Mukherjee
Part III High dimensional time series
7. Functional time series, S. Hörmann and P. Kokoszka
8. Covariance matrix estimation in Time Series, W. B. Wu and H. Xiao
Part IV Time series and quantile regression
9. Time series quantile regressions, Z. Xiao
Part V Biostatistical applications
10. Frequency domain techniques in the analysis of DNA sequences, D. Stoffer
11. Spatial time series modelling for fMRI data analysis in neurosciences, T. Ozaki
12. Count time series models, K. Fokianos
Part VI Nonstationary time series
13. Locally stationary processes, R. Dahlhaus
14. Analysis of multivariate non-stationary time series using the localised Fourier Library,
15. An alternative perspective on stochastic coefficient regression models, S. Subba Rao
Part VII Spatio-Temporal Time Series
16. Hierarachical Bayesian models for space-time air pollution data, S. Sahu
17. Karhunen-Loeve expansion for temporal and spatio-temporal processes, L. Fontanella
and L. Ippoliti
18. Statistical analysis of spatio-temporal models and their applications, T. Subba Rao and
Part VIII Continuous time series
19. Lévy-driven time series models for financial data, P. Brockwell and A. Lindner
20. Discrete and continuous time extremes of stationary processes, K. F. Turkman
Part IX Spectral and Wavelet Methods
21. The estimation of Frequency, B. G. Quinn
22. A wavelet varian
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
Statisticians and scientists in various disciplines who use statistical methodology in their work
- No. of pages:
- © North Holland 2012
- 18th May 2012
- North Holland
- eBook ISBN:
- Hardcover ISBN:
- Paperback ISBN:
"Referring to earlier volumes in the venerable series Handbook of Statistics- -v.3 (1983) and v.5 (1985)--the three editors preface this 30th volume by describing the explosion of developments since those books were published. Initial chapters cover topics that were in their infancy 25 years ago, including bootstrap methods and tests for linearity of a time series. Following is coverage of methods of modeling nonlinear time series, functional data and high-dimensional time series, applications to biological and neurological sciences, nonstationary time series, spatio- temporal models, continuous time series, and spectral and wavelet methods for the analysis of signals, among other topics. The editors are affiliated as follows: Tata Subba Rao (U. of Manchester, UK), Suhasini Subba Rao (Texas A&M U., US) and C.R. Rao (U. of Hyderabad Campus, India)." --Reference and Research Book News, October 2012
School of Mathematics, University of Manchester, UK and C.R.Rao's Advanced Institute of Mathematics, Statistics and Computer Science ((C.R.Rao AIMSCS), Hyderabad, India
C. R. Rao, born in India, is one of this century's foremost statisticians, and received his education in statistics at the Indian Statistical Institute (ISI), Calcutta. He is Emeritus Holder of the Eberly Family Chair in Statistics at Penn State and Director of the Center for Multivariate Analysis. He has long been recognized as one of the world's top statisticians, and has been awarded 34 honorary doctorates from universities in 19 countries spanning 6 continents. His research has influenced not only statistics, but also the physical, social and natural sciences and engineering.
In 2011 he was recipient of the Royal Statistical Society's Guy Medal in Gold which is awarded triennially to those "who are judged to have merited a signal mark of distinction by reason of their innovative contributions to the theory or application of statistics". It can be awarded both to fellows (members) of the Society and to non-fellows. Since its inception 120 years ago the Gold Medal has been awarded to 34 distinguished statisticians. The first medal was awarded to Charles Booth in 1892. Only two statisticians, H. Cramer (Norwegian) and J. Neyman (Polish), outside Great Britain were awarded the Gold medal and C. R. Rao is the first non-European and non-American to receive the award.
Other awards he has received are the Gold Medal of Calcutta University, Wilks Medal of the American Statistical Association, Wilks Army Medal, Guy Medal in Silver of the Royal Statistical Society (UK), Megnadh Saha Medal and Srinivasa Ramanujan Medal of the Indian National Science Academy, J.C.Bose Gold Medal of Bose Institute and Mahalanobis Centenary Gold Medal of the Indian Science Congress, the Bhatnagar award of the Council of Scientific and Industrial Research, India and the Government of India honored him with the second highest civilian award, Padma Vibhushan, for “outstanding contributions to Science and Engineering / Statistics”, and also instituted a cash award in honor of C R Rao, “to be given once in two years to a young statistician for work done during the preceding 3 years in any field of statistics”.
For his outstanding achievements Rao has been honored with the establishment of an institute named after him, C.R.Rao Advanced Institute for Mathematics, Statistics and Computer Science, in the campus of the University of Hyderabad, India.
The Pennsylvania State University, University Park, PA, USA