Rao T.S., Rao S.S., Rao C.R. (Eds.) Handbook of Statistics 30. Time Series Analysis: Methods and Applications

North Holland, 2012. — 730 p.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 methodologyDiscusses a wide variety of diverse applications and recent developmentsContributors are internationally renowened experts in their respective areasPreface to Handbook Volume – 30
Contributors: Vol. 30
Bootstrap Methods for Time Series
Testing Time Series Linearity: Traditional and Bootstrap Methods
The Quest for Nonlinearity in Time Series
Modelling Nonlinear and Nonstationary Time Series
Markov Switching Time Series Models
A Review of Robust Estimation under Conditional Heteroscedasticity
Functional Time Series
Covariance Matrix Estimation in Time Series
Time Series Quantile Regressions
Frequency Domain Techniques in the Analysis of DNA Sequences
Spatial Time Series Modeling for fMRI Data Analysis in Neurosciences
Count Time Series Models
Locally Stationary Processes
Analysis of Multivariate Nonstationary Time Series Using the Localized Fourier Library
An Alternative Perspective on Stochastic Coefficient Regression Models
Hierarchical Bayesian Models for Space–Time Air Pollution Data
Karhunen–Loéve Expansion of Temporal and Spatio-Temporal Processes
Statistical Analysis of Spatio-Temporal Models and Their Applications
Lévy-Driven Time Series Models for Financial Data
Discrete and Continuous Time Extremes of Stationary Processes
The Estimation of Frequency
A Wavelet Variance Primer
Time Series Analysis with R
Index