Time Series Analysis -- Forecasting and Control (English Version, 3rd Edition)

Author: George E. P. Box, Gwilym M. Jenkins, Gregory C. Reinsel
Publisher:
Publish Date: 2005-09-01
Features: Time series analysis is a highly practical and rapidly developing data analysis technique that is now widely applied in various fields such as industrial quality control, bio-genetic engineering, and financial data analysis. The development of all this cannot be mentioned without G.E.P. Box and G.M. Jenkins, as well as their co-authored Time Series Analysis—Forecasting and Control, published before 1970. Due to their significant contributions to time series data analysis, the ARIMA model proposed in this book is named the Box-Jenkins model. In this classic work on time series analysis, several renowned statisticians use extremely accessible language, supported by numerous examples, to explain the essence of time series analysis in a clear, concise, and vivid manner. This allows readers to quickly grasp practical techniques and appreciate the intuitive yet profound ideas without getting bogged down in complex mathematical derivations. It is believed that every reader who studies this book will benefit greatly. Since its first publication in the early 1970s, this book has been continuously revised and reprinted, becoming a model of classic and authoritative works in the field of time series analysis. The book covers the establishment of random (statistical) models for time series and their applications in many important areas, including forecasting, model description, estimation, identification, and diagnostics, the identification, fitting, and testing of transfer functions for dynamic relationships, modeling the impact of intervention events, and process control, among other topics. The book is written in a concise manner, emphasizing practical techniques and accompanied by numerous examples. It can serve as a textbook for senior undergraduate or graduate students in statistics and related fields, as well as a reference for professional statisticians.