Time Series Analysis: Forecasting and ControlHolden-Day, 1976 - 575 pages Table of Contents Preface 1 Introduction 1 2 Autocorrelation Function and Spectrum of Stationary Processes 21 3 Linear Stationary Models 46 4 Linear Nonstationary Models 89 5 Forecasting 131 6 Model Identification 183 7 Model Estimation 224 8 Model Diagnostic Checking 308 9 Seasonal Models 327 10 Transfer Function Models 373 11 Identification, Fitting, and Checking of Transfer Function Models 407 12 Intervention Analysis Models and Outlier Detection 462 13 Aspects of Process Control 483 Collection of Tables and Charts 533 Collection of Time Series Used for Examples in the Text and in Exercises 540 References 556 Exercises and Problems 569 Index 589. |
Table des matières
PREFACE | 1 |
STOCHASTIC MODELS AND THEIR | 21 |
Positive definiteness and the autocovariance matrix | 28 |
Droits d'auteur | |
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Autres éditions - Tout afficher
Time Series Analysis: Forecasting and Control George E. P. Box,Gwilym M. Jenkins Affichage d'extraits - 1976 |
Time Series Analysis: Forecasting and Control George E. P. Box,Gwilym M. Jenkins Affichage d'extraits - 1970 |
Time Series Analysis: Forecasting and Control George E. P. Box,Gwilym M. Jenkins Affichage d'extraits - 1970 |
Expressions et termes fréquents
a₁ action appropriate approximate assumed autocorrelation function autocovariance autoregressive autoregressive process behavior calculation Chapter checking close coefficients computed conditional consider constant correlation corresponding covariance defined derivatives described deviation difference equation discussed distribution effect equal error estimates example expected exponentially expression Figure fitted follows forecast function given Hence identification illustrate indicated initial input integrated interval invertibility iteration lead least squares likelihood limits linear matrix mean method needed noise Normal observations obtained occur operator optimal origin output parameters partial particular period plotted possible practice probability region represented residuals response roots sample scheme shown shows solution standard stationary stochastic substituting sum of squares Suppose Table transfer function unit values variance w₁ weights write written X₁ Y₁ Z₁ zero