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1 Stationary Time Series.- 2 Hilbert Spaces.- 3 Stationary ARMA Processes.- 4 The Spectral Representation of a Stationary Process.- 5 Prediction of Stationary Processes.- 6* Asymptotic Theory.- 7 Estimation of the Mean and the Autocovariance Function.- 8 Estimation for ARMA Models.- 9 Model Building and Forecasting with ARIMA Processes.- 10 Inference for the Spectrum of a Stationary Process.- 11 Multivariate Time Series.- 12 State-Space Models and the Kalman Recursions.- 13 Further Topics.- Appendix: Data Sets.
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Eric R. Ziegel
Winthrop University
Peter J. Brockwell
Colorado State University
Richard A. Davis
City University of New York
Technometrics
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Ziegel et al. (Sat,) studied this question.
synapsesocial.com/papers/6a0874d01e8b9db648de0c95 — DOI: https://doi.org/10.2307/1270070