LEADER 04970nam 2200697Ia 450 001 9911019862403321 005 20200520144314.0 010 $a9786612307607 010 $a9781282307605 010 $a1282307606 010 $a9780470316429 010 $a047031642X 010 $a9780470317136 010 $a0470317132 035 $a(CKB)1000000000687554 035 $a(EBL)469488 035 $a(OCoLC)264615243 035 $a(SSID)ssj0000340643 035 $a(PQKBManifestationID)11253299 035 $a(PQKBTitleCode)TC0000340643 035 $a(PQKBWorkID)10408068 035 $a(PQKB)10893017 035 $a(MiAaPQ)EBC469488 035 $a(PPN)159306280 035 $a(Perlego)2772237 035 $a(EXLCZ)991000000000687554 100 $a19800319d1970 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aMultiple time series /$fE. J. Hannan 210 $aNew York $cWiley$d1970 215 $a1 online resource (552 p.) 225 1 $aWiley series in probability and mathematical statistics 300 $aDescription based upon print version of record. 311 08$a9780471348054 311 08$a0471348058 320 $aIncludes bibliography: p. 519-527. 327 $aMultiple Time Series; Contents; PART I. BASIC THEORY; CHAPTER I. INTRODUCTORY THEORY; 1. Introduction; 2. Differentiation and Integration of Stochastic Processes; 3. Some Special Models; 4. Stationary Processes and their Covariance Structure; 5. Higher Moments; 6. Generalized Random Processes; EXERCISES; APPENDIX; CHAPTER II. THE SPECTRAL THEORY OF VECTOR PROCESSES; 1. Introduction; 2. The Spectral Theorems for Continuous-Time Stationary Processes; 3. Sampling a Continuous-Time Process. Discrete Time Processes; 4. Linear Filters; 5 . Some Special Models 327 $a6. Some Spectral Theory for Nonstationary Processes7. Nonlinear Transformations of Random Processes; 8. Higher Order Spectra; 9. Spectral Theory for GRP; 10. Spectral Theories for Homogeneous Random Processes on Other Spaces; 11. Filters, General Theory; EXERCISES; APPENDIX; CHAPTER III. PREDICTION THEORY AND SMOOTHING; 1. Introduction; 2. Vector Discrete-Time Prediction for Rational Spectra; 3. The General Theory for Stationary, Discrete-Time, Scalar Processes; 4. The General Theory for Stationary, Continuous-Time, Scalar Processes; 5. Vector Discrete-Time Prediction 327 $a6. Problems of Interpolation7. Smoothing and Signal Measurement; 8. Kalman Filtering; 9. Smoothing Filters; EXERCISES; PART II. INFERENCE; CHAPTER IV. THE LAWS OF LARGE NUMBERS AND THE CENTRAL LIMIT THEOREM; 1. Introduction; 2. Strictly Stationary Processes. Ergodic Theory; 3. Second-Order Stationary Processes. Ergodic Theory; 4. The Central Limit Theorem; EXERCISES; APPENDIX; CHAPTER V. INFERENCE ABOUT SPECTRA; 1. Introduction; 2. The Finite Fourier Transform; 3. Alternative Computational Procedures for the FFT; 4. Estimates of Spectral for large Nand N/M 327 $a5. The Asymptotic Distribution of Spectral Estimates6. Complex Multivariate Analysis; EXERCISES; APPENDIX; CHAPTER VI. INFERENCE FOR RATIONAL SPECTRA; 1. Introduction; 2. Inference for Autoregressive Models. Asymptotic Theory; 3. Inference for Autoregressive Models. Some Exact Theory; 4. Moving Average and Mixed Autoregressive, Moving Average Models. Introduction; 5. The Estimation of Moving Average and Mixed Moving Average Autoregressive Models Using Spectral Methods; 6. General Theories of Estimation for Finite Parameter Models; 7. Tests of Goodness of Fit 327 $a8. Continuous-Time Processes and Discrete ApproximationsEXERCISES; APPENDIX; CHAPTER VII. REGRESSION METHODS; 1. Introduction; 2. The Efficiency of Least Squares. Fixed Sample Size; 3. The Efficiency of Least Squares. Asymptotic Theory; 4. The Efficient Estimation of Regressions; 5. The Effects of Regression Procedures on Analysis of Residuals; 6. Tests for Periodicities; 7. Distributed Lag Relationships; EXERCISES; APPENDIX; MATHEMATICAL APPENDIX; BIBLIOGRAPHY; TABLE OF NOTATIONS; INDEX 330 8 $aThe Wiley Series in Probability and Statistics is a collection of topics of current research interests in both pure and applied statistics and probability developments in the field and classical methods. This series provides essential and invaluable reading for all statisticians, whether in academia, industry, government, or research. 410 0$aWiley series in probability and mathematical statistics. 606 $aMathematical statistics 606 $aTime-series analysis 615 0$aMathematical statistics. 615 0$aTime-series analysis. 676 $a519.232 676 $a519.8 700 $aHannan$b E. J$g(Edward James),$f1921-$021010 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911019862403321 996 $aMultiple Time Series$9436679 997 $aUNINA