## Introduction to Time Series Analysis and ForecastingAn accessible introduction to the most current thinking in and practicality of forecasting techniques in the context of time-oriented data. Analyzing time-oriented data and forecasting are among the most important problems that analysts face across many fields, ranging from finance and economics to production operations and the natural sciences. As a result, there is a widespread need for large groups of people in a variety of fields to understand the basic concepts of time series analysis and forecasting. Seven easy-to-follow chapters provide intuitive explanations and in-depth coverage of key forecasting topics, including: -
Regression-based methods, heuristic smoothing methods, and general time series models -
Basic statistical tools used in analyzing time series data -
Metrics for evaluating forecast errors and methods for evaluating and tracking forecasting performance over time -
Cross-section and time series regression data, least squares and maximum likelihood model fitting, model adequacy checking, prediction intervals, and weighted and generalized least squares -
Exponential smoothing techniques for time series with polynomial components and seasonal data -
Forecasting and prediction interval construction with a discussion on transfer function models as well as intervention modeling and analysis -
Multivariate time series problems, ARCH and GARCH models, and combinations of forecasts
The intricate role of computer software in successful time series analysis is acknowledged with the use of Minitab, JMP, and SAS software applications, which illustrate how the methods are imple-mented in practice. An extensive FTP site is available for readers to obtain data sets, Microsoft Office PowerPoint slides, and selected answers to problems in the book. Requiring only a basic working knowledge of statistics and complete with exercises at the end of each chapter as well as examples from a wide array of fields, |

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### Contents

Statistics Background for Forecasting | |

Performance | |

Exponential Smoothing Methods | |

Autoregressive Integrated Moving Average ARIMA | |

Transfer Functions and Intervention Models | |

Survey of Other Forecasting Methods | |

Appendix A Statistical Tables | |

### Other editions - View all

Introduction to Time Series Analysis and Forecasting Douglas C. Montgomery,Cheryl L. Jennings,Murat Kulahci No preview available - 2008 |