Introduction to time series and forecasting. 3rd edition.

*(English)*Zbl 1355.62001
Springer Texts in Statistics. Cham: Springer (ISBN 978-3-319-29852-8/hbk; 978-3-319-29854-2/ebook). xiv, 425 p. (2016).

For the first and second editions of this book from 1996 and 2002 resp. see [Zbl 0868.62067] and [Zbl 0994.62085]. The references in this third edition given at the end are carefully updated to include also hints to quite recent research results.

Publisher’s description: “This book is aimed at the reader who wishes to gain a working knowledge of time series and forecasting methods as applied to economics, engineering and the natural and social sciences. It assumes knowledge only of basic calculus, matrix algebra and elementary statistics. This third edition contains detailed instructions for the use of the professional version of the Windows-based computer package ITSM2000, now available as a free download from the Springer Extras website. The logic and tools of time series model-building are developed in detail. Numerous exercises are included and the software can be used to analyze and forecast data sets of the user’s own choosing. The book can also be used in conjunction with other time series packages such as those included in R. The programs in ITSM2000 however are menu-driven and can be used with minimal investment of time in the computational details. The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Many additional special topics are also covered. New to this edition are a chapter devoted to financial time series, introductions to Brownian motion, Lévy processes and Itô calculus, and an expanded section on continuous-time ARMA processes.”

Publisher’s description: “This book is aimed at the reader who wishes to gain a working knowledge of time series and forecasting methods as applied to economics, engineering and the natural and social sciences. It assumes knowledge only of basic calculus, matrix algebra and elementary statistics. This third edition contains detailed instructions for the use of the professional version of the Windows-based computer package ITSM2000, now available as a free download from the Springer Extras website. The logic and tools of time series model-building are developed in detail. Numerous exercises are included and the software can be used to analyze and forecast data sets of the user’s own choosing. The book can also be used in conjunction with other time series packages such as those included in R. The programs in ITSM2000 however are menu-driven and can be used with minimal investment of time in the computational details. The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Many additional special topics are also covered. New to this edition are a chapter devoted to financial time series, introductions to Brownian motion, Lévy processes and Itô calculus, and an expanded section on continuous-time ARMA processes.”

Reviewer: Hans-Jürgen Schmidt (Potsdam)

##### MSC:

62-01 | Introductory exposition (textbooks, tutorial papers, etc.) pertaining to statistics |

62M10 | Time series, auto-correlation, regression, etc. in statistics (GARCH) |

62M20 | Inference from stochastic processes and prediction |

62-04 | Software, source code, etc. for problems pertaining to statistics |

62M15 | Inference from stochastic processes and spectral analysis |

62P05 | Applications of statistics to actuarial sciences and financial mathematics |

62P20 | Applications of statistics to economics |

62P25 | Applications of statistics to social sciences |

62P30 | Applications of statistics in engineering and industry; control charts |

62H05 | Characterization and structure theory for multivariate probability distributions; copulas |

62P35 | Applications of statistics to physics |

60G25 | Prediction theory (aspects of stochastic processes) |

60J65 | Brownian motion |