Time Series Analysis: Forecasting and ControlHolden-Day, 1976 - 575 páginas 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. |
Conteúdo
PREFACE | 1 |
STOCHASTIC MODELS AND THEIR | 21 |
LINEAR STATIONARY MODELS | 46 |
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a₁ action appropriate approximate assumed autocorrelation function autocovariance autoregressive process behavior calculation Chapter close coefficients computed conditional consider continuous corresponding covariance defined derivatives described deviation difference difference equation discrete discussed distribution effect equal equation error estimates example expected exponentially expression Figure fitted follows forecast function given Hence identification illustrate indicated initial input interval invertibility iteration lead least squares likelihood limits linear matrix mean method moving average Normal observations obtained occur operator origin output parameters particular period possible practice probability procedure region represented residuals response roots sample scheme shown shows solution standard starting stationary stochastic substituting sum of squares Suppose Table transfer function model unit values variance w₁ weights write written X₁ Y₁ Z₁ zero