Time Series: Theory and Methods

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Springer Science & Business Media, May 13, 2009 - Mathematics - 580 pages
This edition contains a large number of additions and corrections scattered throughout the text, including the incorporation of a new chapter on state-space models. The companion diskette for the IBM PC has expanded into the software package ITSM: An Interactive Time Series Modelling Package for the PC, which includes a manual and can be ordered from Springer-Verlag. * We are indebted to many readers who have used the book and programs and made suggestions for improvements. Unfortunately there is not enough space to acknowledge all who have contributed in this way; however, special mention must be made of our prize-winning fault-finders, Sid Resnick and F. Pukelsheim. Special mention should also be made of Anthony Brockwell, whose advice and support on computing matters was invaluable in the preparation of the new diskettes. We have been fortunate to work on the new edition in the excellent environments provided by the University of Melbourne and Colorado State University. We thank Duane Boes particularly for his support and encouragement throughout, and the Australian Research Council and National Science Foundation for their support of research related to the new material. We are also indebted to Springer-Verlag for their constant support and assistance in preparing the second edition. Fort Collins, Colorado P. J. BROCKWELL November, 1990 R. A. DAVIS * /TSM: An Interactive Time Series Modelling Package for the PC by P. J. Brockwell and R. A. Davis. ISBN: 0-387-97482-2; 1991.

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6 2Convergence in rthMeanr
Maximum Likelihood ARMASpectral Estimators
Stationary Time Series
Estimation of the Mean and the Autocovariance
2 5Projection
2 8Fourier Series 2 9 Hilbert Space Isomorphisms
Problems Chapter
8 6Recursive Calculationof theLikelihood of an Arbitrary
ARMA Processes
9 2Identification Techniques
9 3Order Selection
9 4Diagnostic Checking

3 2Moving Average Processes of Infinite Order
3 3Computing the Autocovariance Functionof an ARMApq Process
The Spectral Representation of a Stationary Process
Chapter 5Prediction of Stationary Processes
5 3Recursive Prediction of an ARMAp q Process
Multivariate Time Series
Chapter 13Further Topics

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