, ,

Time Series Analysis: Methods and Applications

Specificaties
Gebonden, blz. | Engels
Elsevier Science | e druk, 2012
ISBN13: 9780444538581
Rubricering
Elsevier Science e druk, 2012 9780444538581
Onderdeel van serie Handbook of Statistics
Verwachte levertijd ongeveer 9 werkdagen

Samenvatting

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.

Specificaties

ISBN13:9780444538581
Taal:Engels
Bindwijze:Gebonden

Inhoudsopgave

1. Bootstrap methods for time series<br>2. Testing time series linearity: traditional and bootstrap methods<br>3. The quest for nonlinearity in Time Series<br>4. Modelling nonlinear and nonstationary time series,<br>5. Markov switching time series models<br>6. A review of robust estimation under conditional heteroscedasticity<br>7. Functional time series<br>8. Covariance matrix estimation in Time Series<br>9. Time series quantile regressions<br>10. Frequency domain techniques in the analysis of DNA sequences<br>11. Spatial time series modelling for fMRI data analysis in neurosciences<br>12. Count time series models<br>13. Locally stationary processes<br>14. Analysis of multivariate non-stationary time series using the localised Fourier Library<br>15. An alternative perspective on stochastic coefficient regression models<br>16. Hierarachical Bayesian models for space-time air pollution data<br>17. Karhunen-Loeve expansion for temporal and spatio-temporal processes<br>18. Statistical analysis of spatio-temporal models and their applications<br>19. Lévy-driven time series models for financial data<br>20. Discrete and continuous time extremes of stationary processesn<br>21. The estimation of Frequency<br>22. A wavelet variance primer<br>23. Time Series Analysis with R

Rubrieken

    Personen

      Trefwoorden

        Time Series Analysis: Methods and Applications