【书名】 Introduction to Time Series and Forecasting<br/>【作者】Peter J. Brockwell  ,Richard A. Davis<br/>【版本】Second Edition<br/>【出版日期】<br/>【文件格式】PDF<br/>【文件大锌2.35M<br/>【页数】449<br/>【ISBN出版号】0-387-95351-5<br/>【资料类别】计量经济学<br/>【影印版】<br/>【是否缺页】否<br/>【目录】Preface vii<br/>1. Introduction 1<br/>2. Stationary Processes 45<br/>3. ARMA Models 83<br/>4. Spectral Analysis 111<br/>5. Modeling and Forecasting with ARMA Processes 137<br/>6. Nonstationary and Seasonal Time Series Models 179<br/>7. Multivariate Time Series 223<br/>8. State-Space Models 259<br/>9. Forecasting Techniques 317<br/>10. Further Topics 331<br/>A. Random Variables and Probability Distributions 369<br/>A.1. Distribution Functions and Expectation 369<br/>A.2. Random Vectors 374<br/>A.3. The Multivariate Normal Distribution 377<br/>Problems 381<br/>Contents xiii<br/>B. Statistical Complements 383<br/>B.1. Least Squares Estimation 383<br/>B.1.1. The Gauss-Markov Theorem 385<br/>B.1.2. Generalized Least Squares 386<br/>B.2. Maximum Likelihood Estimation 386<br/>B.2.1. Properties of Maximum Likelihood Estimators 387<br/>B.3. Confidence Intervals 388<br/>B.3.1. Large-Sample Confidence Regions 388<br/>B.4. Hypothesis Testing 389<br/>B.4.1. Error Probabilities 390<br/>B.4.2. Large-Sample Tests Based on Confidence Regions 390<br/>C. Mean Square Convergence 393<br/>C.1. The Cauchy Criterion 393<br/>D. An ITSM Tutorial 395<br/>D.1. Getting Started 396<br/>D.1.1. Running ITSM 396<br/>D.2. Preparing Your Data for Modeling 396<br/>D.2.1. Entering Data 397<br/>D.2.2. Information 397<br/>D.2.3. Filing Data 397<br/>D.2.4. Plotting Data 398<br/>D.2.5. Transforming Data 398<br/>D.3. Finding a Model for Your Data 403<br/>D.3.1. Autofit 403<br/>D.3.2. The Sample ACF and PACF 403<br/>D.3.3. Entering a Model 404<br/>D.3.4. Preliminary Estimation 406<br/>D.3.5. The AICC Statistic 408<br/>D.3.6. Changing Your Model 408<br/>D.3.7. Maximum Likelihood Estimation 409<br/>D.3.8. Optimization Results 410<br/>D.4. Testing Your Model 411<br/>D.4.1. Plotting the Residuals 412<br/>D.4.2. ACF/PACF of the Residuals 412<br/>D.4.3. Testing for Randomness of the Residuals 414<br/>D.5. Prediction 415<br/>D.5.1. Forecast Criteria 415<br/>D.5.2. Forecast Results 415<br/>xiv Contents<br/>D.6. Model Properties 416<br/>D.6.1. ARMA Models 417<br/>D.6.2. Model ACF, PACF 418<br/>D.6.3. Model Representations 419<br/>D.6.4. Generating Realizations of a Random Series 420<br/>D.6.5. Spectral Properties 421<br/>D.7. Multivariate Time Series 421<br/>References 423<br/>Index<br/>