Time Series: Theory and MethodsThis 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. |
Contents
CHAPTER | 1 |
1 | 11 |
CHAPTER | 19 |
1 6 | 27 |
2 1 | 41 |
2 3 | 47 |
2 5 | 58 |
2 8 | 65 |
5 4 | 182 |
CHAPTER | 198 |
6 3 | 204 |
Estimation of the Mean and the Autocovariance Function | 218 |
CHAPTER 8 | 238 |
CHAPTER 9 | 273 |
CHAPTER 10 | 330 |
Maximum Likelihood ARMA Spectral Estimators | 365 |
3 1 | 77 |
CHAPTER 4 | 114 |
4 4 | 121 |
CHAPTER 5 | 166 |
3 | 175 |
CHAPTER 11 | 401 |
CHAPTER 12 | 463 |
CHAPTER 13 | 506 |
Data Sets 555 | 554 |
| 567 | |
Other editions - View all
Time Series: Theory and Methods: Theory and Methods Peter J. Brockwell,Richard A. Davis Limited preview - 1991 |
Common terms and phrases
a₁ absolutely summable AICC algorithm approximation AR(p ARMA process ARMA(p asymptotic autocovariance function autoregressive best linear predictor coefficients complex-valued components compute converges Corollary covariance matrix denote difference equations dZ(v Example Figure follows Fourier frequency Gaussian H₁ Hence Hilbert space independent inner product inner-product space integer L²(F m₁ maximum likelihood estimators mean squared error mean zero moving average non-negative definite observations obtain orthogonal-increment process orthonormal parameters partial autocorrelation periodogram polynomial prediction Problem process defined program PEST PROOF properties Proposition random variables random vector recursions Remark sample autocorrelation function satisfies Section sp{X spectral density spectral distribution function spectral representation state-space model stationary process Theorem U₁ uncorrelated V₁ values variance W₁ white noise X₁ X₁₁ Xn+1 Xn+h Y₁ Z₁ π π Σ Σ σ²