Customer Reviews

Forecasting with Dynamic Regression Models

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It is an excellent book for understanding time series analysis, well written and clearly explained. Readers should have some knowledge of univariate ARIMA model but no expertise is required. The book focuses on how, why, and when to combine the effect of other variables and the univariate ARIMA model. The suggested methods are demonstrated by a well-explained example. The author describes each step in the analysis in detail, this greatly helps in understanding the logic. Therefore, I highly recommend this book for students or persons who have a preliminary knowledge of the time series analysis technique, and who want to develop a more in-depth understanding of the subject. In addition, it is a must-have reference book for all time-series analyst.

I was assigned to develop a stochastic model for air pollution (well, back to 3 weeks before, I had no idea what time series analysis was !!!). After spend some time searching around for an easy-to-understand textbook dealing with time series data, I found this book is the best. It is comprehensive and clearly explain with many good excercises. What you need is some basic knowledge in ARIMA (which could be find from general econometrics textbook or SPSS guideline) and simple linear regression and then you will love this book as I am now.

Being a noive to Box Jenkin method, the clear, and well organized exposition of this book took me step by step to a firm understanding of the method within a short time span, and keys to practice it. After finishing reading a copy from the library, I find it worths to purchase one for reference.