{"product_id":"time-series-analysis-9781118675021","title":"Time Series Analysis","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e\u003cb\u003ePraise for the \u003ci\u003eFourth Edition \u003c\/i\u003e\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe book follows faithfully the style of the original edition. The approach is heavily motivated by real-world time series, and by developing a complete approach to model building, estimation, forecasting and control.\u003cbr\u003e\u003cb\u003eMathematical Reviews\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eBridging classical models and modern topics, the \u003ci\u003eFifth Edition\u003c\/i\u003e of\u003ci\u003e Time Series Analysis: Forecasting and Control\u003c\/i\u003e maintains a balanced presentation of the tools for modeling and analyzing time series. Also describing the latest developments that have occurred in the field over the past decade through applications from areas such as business, finance, and engineering, the \u003ci\u003eFifth Edition\u003c\/i\u003e continues to serve as one of the most influential and prominent works on the subject.\u003c\/p\u003e \u003cp\u003e\u003ci\u003eTime Series Analysis: Forecasting and Control, Fifth Edition \u003c\/i\u003eprovides a clearly written exploration of the key methods for building, classifying, testing, and analyzing stochastic \u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003ePREFACE TO THE FIFTH EDITION xix\u003c\/p\u003e \u003cp\u003ePREFACE TO THE FOURTH EDITION xxiii\u003c\/p\u003e \u003cp\u003ePREFACE TO THE THIRD EDITION xxv\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Introduction 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 Five Important Practical Problems 2\u003c\/p\u003e \u003cp\u003e1.2 Stochastic and Deterministic Dynamic Mathematical Models 6\u003c\/p\u003e \u003cp\u003e1.3 Basic Ideas in Model Building 14\u003c\/p\u003e \u003cp\u003eAppendix A1.1 Use of the R Software 17\u003c\/p\u003e \u003cp\u003eExercises 18\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART ONE STOCHASTIC MODELS AND THEIR FORECASTING 19\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Autocorrelation Function and Spectrum of Stationary Processes 21\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Autocorrelation Properties of Stationary Models 21\u003c\/p\u003e \u003cp\u003e2.2 Spectral Properties of Stationary Models 34\u003c\/p\u003e \u003cp\u003eAppendix A2.1 Link Between the Sample Spectrum and Autocovariance\u003c\/p\u003e \u003cp\u003eFunction Estimate 43\u003c\/p\u003e \u003cp\u003eExercises 44\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Linear Stationary Models 47\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 General Linear Process 47\u003c\/p\u003e \u003cp\u003e3.2 Autoregressive Processes 54\u003c\/p\u003e \u003cp\u003e3.3 Moving Average Processes 68\u003c\/p\u003e \u003cp\u003e3.4 Mixed Autoregressive--Moving Average Processes 75\u003c\/p\u003e \u003cp\u003eAppendix A3.1 Autocovariances Autocovariance Generating Function and Stationarity Conditions for a General Linear Process 82\u003c\/p\u003e \u003cp\u003eAppendix A3.2 Recursive Method for Calculating Estimates of Autoregressive Parameters 84\u003c\/p\u003e \u003cp\u003eExercises 86\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Linear Nonstationary Models 88\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Autoregressive Integrated Moving Average Processes 88\u003c\/p\u003e \u003cp\u003e4.2 Three Explicit Forms for the ARIMA Model 97\u003c\/p\u003e \u003cp\u003e4.3 Integrated Moving Average Processes 106\u003c\/p\u003e \u003cp\u003eAppendix A4.1 Linear Difference Equations 116\u003c\/p\u003e \u003cp\u003eAppendix A4.2 IMA(0 1 1) Process with Deterministic Drift 121\u003c\/p\u003e \u003cp\u003eAppendix A4.3 ARIMA Processes with Added Noise 122\u003c\/p\u003e \u003cp\u003eExercises 126\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Forecasting 129\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Minimum Mean Square Error Forecasts and Their Properties 129\u003c\/p\u003e \u003cp\u003e5.2 Calculating Forecasts and Probability Limits 135\u003c\/p\u003e \u003cp\u003e5.3 Forecast Function and Forecast Weights 139\u003c\/p\u003e \u003cp\u003e5.4 Examples of Forecast Functions and Their Updating 144\u003c\/p\u003e \u003cp\u003e5.5 Use of State-Space Model Formulation for Exact Forecasting 155\u003c\/p\u003e \u003cp\u003e5.6 Summary 162\u003c\/p\u003e \u003cp\u003eAppendix A5.1 Correlation Between Forecast Errors 164\u003c\/p\u003e \u003cp\u003eAppendix A5.2 Forecast Weights for any Lead Time 166\u003c\/p\u003e \u003cp\u003eAppendix A5.3 Forecasting in Terms of the General Integrated Form 168\u003c\/p\u003e \u003cp\u003eExercises 174\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART TWO STOCHASTIC MODEL BUILDING 177\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Model Identification 179\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Objectives of Identification 179\u003c\/p\u003e \u003cp\u003e6.2 Identification Techniques 180\u003c\/p\u003e \u003cp\u003e6.3 Initial Estimates for the Parameters 194\u003c\/p\u003e \u003cp\u003e6.4 Model Multiplicity 202\u003c\/p\u003e \u003cp\u003eAppendix A6.1 Expected Behavior of the Estimated Autocorrelation Function for a Nonstationary Process 206\u003c\/p\u003e \u003cp\u003eExercises 207\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Parameter Estimation 209\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Study of the Likelihood and Sum-of-Squares Functions 209\u003c\/p\u003e \u003cp\u003e7.2 Nonlinear Estimation 226\u003c\/p\u003e \u003cp\u003e7.3 Some Estimation Results for Specific Models 236\u003c\/p\u003e \u003cp\u003e7.4 Likelihood Function Based on the State-Space Model 242\u003c\/p\u003e \u003cp\u003e7.5 Estimation Using Bayes’ Theorem 245\u003c\/p\u003e \u003cp\u003eAppendix A7.1 Review of Normal Distribution Theory 251\u003c\/p\u003e \u003cp\u003eAppendix A7.2 Review of Linear Least-Squares Theory 256\u003c\/p\u003e \u003cp\u003eAppendix A7.3 Exact Likelihood Function for Moving Average and Mixed Processes 259\u003c\/p\u003e \u003cp\u003eAppendix A7.4 Exact Likelihood Function for an Autoregressive Process 266\u003c\/p\u003e \u003cp\u003eAppendix A7.5 Asymptotic Distribution of Estimators for Autoregressive Models 274\u003c\/p\u003e \u003cp\u003eAppendix A7.6 Examples of the Effect of Parameter Estimation Errors on Variances of Forecast Errors and Probability Limits for Forecasts 277\u003c\/p\u003e \u003cp\u003eAppendix A7.7 Special Note on Estimation ofMoving Average Parameters 280\u003c\/p\u003e \u003cp\u003eExercises 280\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Model Diagnostic Checking 284\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Checking the Stochastic Model 284\u003c\/p\u003e \u003cp\u003e8.2 Diagnostic Checks Applied to Residuals 287\u003c\/p\u003e \u003cp\u003e8.3 Use of Residuals to Modify the Model 301\u003c\/p\u003e \u003cp\u003eExercises 303\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Analysis of Seasonal Time Series 305\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 Parsimonious Models for Seasonal Time Series 305\u003c\/p\u003e \u003cp\u003e9.2 Representation of the Airline Data by a Multiplicative (0 1 1) × (0 1 1)12 Model 310\u003c\/p\u003e \u003cp\u003e9.3 Some Aspects of More General Seasonal ARIMA Models 325\u003c\/p\u003e \u003cp\u003e9.4 Structural Component Models and Deterministic Seasonal Components 331\u003c\/p\u003e \u003cp\u003e9.5 Regression Models with Time Series Error Terms 339\u003c\/p\u003e \u003cp\u003eAppendix A9.1 Autocovariances for Some Seasonal Models 345\u003c\/p\u003e \u003cp\u003eExercises 349\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Additional Topics and Extensions 352\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 Tests for Unit Roots in ARIMA Models 353\u003c\/p\u003e \u003cp\u003e10.2 Conditional Heteroscedastic Models 361\u003c\/p\u003e \u003cp\u003e10.3 Nonlinear Time Series Models 377\u003c\/p\u003e \u003cp\u003e10.4 Long Memory Time Series Processes 385\u003c\/p\u003e \u003cp\u003eExercises 392\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART THREE TRANSFER FUNCTION AND MULTIVARIATE MODEL BUILDING 395\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Transfer Function Models 397\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1 Linear Transfer Function Models 397\u003c\/p\u003e \u003cp\u003e11.2 Discrete Dynamic Models Represented by Difference Equations 404\u003c\/p\u003e \u003cp\u003e11.3 Relation Between Discrete and Continuous Models 414\u003c\/p\u003e \u003cp\u003eAppendix A11.1 Continuous Models with Pulsed Inputs 420\u003c\/p\u003e \u003cp\u003eAppendix A11.2 Nonlinear Transfer Functions and Linearization 424\u003c\/p\u003e \u003cp\u003eExercises 426\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Identification Fitting and Checking of Transfer Function Models 428\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12.1 Cross-Correlation Function 429\u003c\/p\u003e \u003cp\u003e12.2 Identification of Transfer Function Models 435\u003c\/p\u003e \u003cp\u003e12.3 Fitting and Checking Transfer Function Models 446\u003c\/p\u003e \u003cp\u003e12.4 Some Examples of Fitting and Checking Transfer Function Models 453\u003c\/p\u003e \u003cp\u003e12.5 Forecasting with Transfer FunctionModels Using Leading Indicators 461\u003c\/p\u003e \u003cp\u003e12.6 Some Aspects of the Design of Experiments to Estimate Transfer Functions 469\u003cbr\u003eAppendix A12.1 Use of Cross-Spectral Analysis for Transfer Function Model Identification 471\u003c\/p\u003e \u003cp\u003eAppendix A12.2 Choice of Input to Provide Optimal Parameter Estimates 473\u003c\/p\u003e \u003cp\u003eExercises 477\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Intervention Analysis Outlier Detection and Missing Values 481\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e13.1 Intervention Analysis Methods 481\u003c\/p\u003e \u003cp\u003e13.2 Outlier Analysis for Time Series 488\u003c\/p\u003e \u003cp\u003e13.3 Estimation for ARMA Models with Missing Values 495\u003c\/p\u003e \u003cp\u003eExercises 502\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Multivariate Time Series Analysis 505\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e14.1 Stationary Multivariate Time Series 506\u003c\/p\u003e \u003cp\u003e14.2 Vector Autoregressive Models 509\u003c\/p\u003e \u003cp\u003e14.3 Vector Moving Average Models 524\u003c\/p\u003e \u003cp\u003e14.4 Vector Autoregressive--Moving Average Models 527\u003c\/p\u003e \u003cp\u003e14.5 Forecasting for Vector Autoregressive--Moving Average Processes 534\u003c\/p\u003e \u003cp\u003e14.6 State-Space Form of the VARMA Model 536\u003c\/p\u003e \u003cp\u003e14.7 Further Discussion of VARMA Model Specification 539\u003c\/p\u003e \u003cp\u003e14.8 Nonstationarity and Cointegration 546\u003c\/p\u003e \u003cp\u003eAppendix A14.1 Spectral Characteristics and Linear Filtering Relations for Stationary Multivariate Processes 552\u003c\/p\u003e \u003cp\u003eExercises 554\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART FOUR DESIGN OF DISCRETE CONTROL SCHEMES 559\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 Aspects of Process Control 561\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e15.1 Process Monitoring and Process Adjustment 562\u003c\/p\u003e \u003cp\u003e15.2 Process Adjustment Using Feedback Control 566\u003c\/p\u003e \u003cp\u003e15.3 Excessive Adjustment Sometimes Required by MMSE Control 580\u003c\/p\u003e \u003cp\u003e15.4 Minimum Cost Control with Fixed Costs of Adjustment and Monitoring 582\u003c\/p\u003e \u003cp\u003e15.5 Feedforward Control 588\u003c\/p\u003e \u003cp\u003e15.6 Monitoring Values of Parameters of Forecasting and Feedback Adjustment Schemes 599\u003c\/p\u003e \u003cp\u003eAppendix A15.1 Feedback Control Schemes Where the Adjustment Variance Is Restricted 600\u003c\/p\u003e \u003cp\u003eAppendix A15.2 Choice of the Sampling Interval 609\u003c\/p\u003e \u003cp\u003eExercises 613\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART FIVE CHARTS AND TABLES 617\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eCOLLECTION OF TABLES AND CHARTS 619\u003c\/p\u003e \u003cp\u003eCOLLECTION OF TIME SERIES USED FOR EXAMPLES IN THE TEXT AND IN EXERCISES 625\u003c\/p\u003e \u003cp\u003eREFERENCES 642\u003c\/p\u003e \u003cp\u003eINDEX 659\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":48866375565655,"sku":"9781118675021","price":114.26,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781118675021.jpg?v=1722278351","url":"https:\/\/bookcurl.com\/products\/time-series-analysis-9781118675021","provider":"Book Curl","version":"1.0","type":"link"}