Introduction to time series modeling - Kitagawa, G. (Genshiro), 1948- (Boca Raton : Chapman & Hall/CRC, 2010)
1. Introduction and preparatory analysis -- 2. The covariance function -- 3. The power spectrum and the periodogram -- 4. Statistical modeling -- 5. The least squares method -- 6. Analysis of time series using ARMA models -- 7. Estimation of an AR model -- 8. The locally stationary AR model -- 9. Analysis of time series with a state-space model -- 10. Estimation of the ARMA model -- 11. Estimation of trends -- 12. The seasonal adjustment model -- 13. Time-varying coefficient AR model -- 14. Non-gaussian state-space model -- 15. The sequential Monte Carlo filter -- 16. Simulation -- A. Algorithms for nonlinear optimization -- B. Derivation of Levinson's algorithm -- C. Derivation of the Kalman filter and smoother algorithms -- D. Algorithm for the Monte Carlo filter.
Includes bibliographical references and index.
Also available as an electronic resource.
Keywords: State-space methods; Time-series analysis