00000nam a22000004a 4500 UP-1686042739785060683 Buklod 20240909133312.0 m o j cr cn |||aaaaa 240906s2013 nju||||go||j| ||||||engdd 9781118619193 (eISBN) UMI DMLR rda eng QA 276 B67 2013eb Box, George E. P. author Time series analysis forecasting and control George E.P. Box, Gwilym M. Jenkins, Gregory C. Reinsel. Hoboken, New Jersey J. Wiley & Sons 2013 ©2008 online resource (xvii, 618 pages) illustrations text rdacontent computer rdamedia online resource rdacarrier Wiley series in probability and statistics UP System perpetual contents Includes bibliographical references (pages 685-699) and index Contents; 1: Introduction; Part One: Stochastic Models and Their Forecasting; 2: Autocorrelation Function and Spectrum of Stationary Processes; 3: Linear Stationary Models; 4: Linear Nonstationary Models; 5: Forecasting; Part Two: Stochastic Model Building; 6: Model Identification; 7: Model Estimation; 8: Model Diagnostic Checking; 9: Seasonal Models; 10: Nonlinear and Long Memory Models; Part Three: Transfer Function and Multivariate Model Building; 11: Transfer Function Models; 12: Identification, Fitting, and Checking of Transfer Function Models; 13: Intervention Analysis Models and Outlier Detection; 14: Multivariate Time Series Analysis; Part Four: Design Discrete Control Schemes; 15: Aspects of Process Control; Part Five: Charts and Tables; Collection of Tables and Charts; Collection of Time Series Used for Examples in the Text and in Exercises; References; Part Six: Exercises and Problems; Index. "A modernized new edition of one of the most trusted books on time series analysis. Since publication of the first edition in 1970, Time Series Analysis has served as one of the most influential and prominent works on the subject. This new edition maintains its balanced presentation of the tools for modelling and analyzing time series and also introduces the latest developments that have occurred n the field over the past decade through applications from areas such as business, finance, and engineering. The Fourth Edition provides a clearly written exploration of the key methods for building, classifying, testing, and analyzing stochastic models for time series as well as their use in five important areas of application: forecasting; determining the transfer function of a system; modelling the effects of intervention events; developing multivariate dynamic models; and designing simple control schemes. Along with these classical uses, modern topics are introduced through the book' new features, which include: A new chapter on multivariate time series analysis, including a discussion of the challenge that arise with their modelling and an outline of the necessary analytical tools. New coverage of forecasting in the design of feedback and feedforward control schemes. A new chapter on nonlinear and long memory models, which explores additional models for application such as heteroscedastic time series, nonlinear time series models, and models for long memory processes. Coverage of structural component models for the modelling, forecasting, and seasonal adjustment of time series. A review of the maximum likelihood estimation for ARMA models with missing values. Numerous illustrations and detailed appendices supplement the book, while extensive references and discussion questions at the end of each chapter facilitate an in-depth understanding of both time-tested and modern concepts. With its focus on practical, rather than heavily mathematical, techniques, Time Series Analysis, Fourth Edition is the upper-undergraduate and graduate levels. this book is also an invaluable reference for applied statisticians, engineers, and financial analysts"-- Provided by publisher Time series analysis. Prediction theory. Transfer functions. Feedback control systems Mathematical models. Jenkins, Gwilym M. author. Reinsel, Gregory C. author. https://doi.org/10.1002/9781118619193 Available for UP System via Wiley Online Library FO UPD DMLR QA 276 B67 2013eb Electronic Resource