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Time Series Analysis : Univariate and Multivariate Methods (2nd Edition), by William W.S. Wei
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With its broad coverage of methodology, this comprehensive book is a useful learning and reference tool for those in applied sciences where analysis and research of time series is useful. Its plentiful examples show the operational details and purpose of a variety of univariate and multivariate time series methods. Numerous figures, tables and real-life time series data sets illustrate the models and methods useful for analyzing, modeling, and forecasting data collected sequentially in time. The text also offers a balanced treatment between theory and applications.
Overview. Fundamental Concepts. Stationary Time Series Models. Nonstationary Time Series Models. Forecasting. Model Identification. Parameter Estimation, Diagnostic Checking, and Model Selection. Seasonal Time Series Models. Testing for a Unit Root. Intervention Analysis and Outlier Detection. Fourier Analysis. Spectral Theory of Stationary Processes. Estimation of the Spectrum. Transfer Function Models. Time Series Regression and GARCH Models. Vector Time Series Models. More on Vector Time Series. State Space Models and the Kalman Filter. Long Memory and Nonlinear Processes. Aggregation and Systematic Sampling in Time Series.
For all readers interested in time series analysis.
- Sales Rank: #188654 in Books
- Published on: 2005-07-17
- Original language: English
- Number of items: 1
- Dimensions: 9.20" h x 1.60" w x 7.00" l, .66 pounds
- Binding: Paperback
- 624 pages
Most helpful customer reviews
26 of 26 people found the following review helpful.
a really nicely written book on multivariate time series
By Michael R. Chernick
This book provides a well-written and rigorous coverage of univariate time series, particularly the time domain models of Box and Jenkins. Its outstanding feature, however, is its treatment of multivariate time series modeling. It is the only book that I know of, that provides a clear and to the point picture of successful multivariate approaches. A little discussion of more recent multivariate advances can be found in Kennedy's 4th edition of his "A Guide to Econometrics".
9 of 10 people found the following review helpful.
Good book for learning time series analysis in full depth
By A Customer
This book gives a thorough analysis of the basis of time series analysis from the basic AR and MA-processes up to ARMA, ARIMA-processes. It also gives you a brief introduction to intervention, seasonal, vector and interruption analyses. A drawback however is the inept use of relevant software to produce more accurate parameter-estimates. I used this book as one of my graduate courses and it gives a proper background to help you understand time series analysis.
4 of 4 people found the following review helpful.
Great book
By Sherry
This is the best book for Time Series. It's well written and full of examples and exercises. Chapter 2 and 3 are the difficult parts. You can read them a few times at first. Then after you finish chapter 4-6, come back to read 2 and 3 again and you will grasp a great deal out of it.
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