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Chapter 1 - Time Series and Their Features
Pages 1-12 - Book chapterAbstract only
Chapter 2 - Transforming Time Series
Pages 13-30 - Book chapterAbstract only
Chapter 3 - ARMA Models for Stationary Time Series
Pages 31-56 - Book chapterAbstract only
Chapter 4 - ARIMA Models for Nonstationary Time Series
Pages 57-69 - Book chapterAbstract only
Chapter 5 - Unit Roots, Difference and Trend Stationarity, and Fractional Differencing
Pages 71-101 - Book chapterAbstract only
Chapter 6 - Breaking and Nonlinear Trends
Pages 103-119 - Book chapterAbstract only
Chapter 7 - An Introduction to Forecasting With Univariate Models
Pages 121-130 - Book chapterAbstract only
Chapter 8 - Unobserved Component Models, Signal Extraction, and Filters
Pages 131-144 - Book chapterAbstract only
Chapter 9 - Seasonality and Exponential Smoothing
Pages 145-160 - Book chapterAbstract only
Chapter 10 - Volatility and Generalized Autoregressive Conditional Heteroskedastic Processes
Pages 161-171 - Book chapterAbstract only
Chapter 11 - Nonlinear Stochastic Processes
Pages 173-199 - Book chapterAbstract only
Chapter 12 - Transfer Functions and Autoregressive Distributed Lag Modeling
Pages 201-210 - Book chapterAbstract only
Chapter 13 - Vector Autoregressions and Granger Causality
Pages 211-231 - Book chapterAbstract only
Chapter 14 - Error Correction, Spurious Regressions, and Cointegration
Pages 233-253 - Book chapterAbstract only
Chapter 15 - Vector Autoregressions With Integrated Variables, Vector Error Correction Models, and Common Trends
Pages 255-279 - Book chapterAbstract only
Chapter 16 - Compositional and Count Time Series
Pages 281-297 - Book chapterAbstract only
Chapter 17 - State Space Models
Pages 299-309 - Book chapterAbstract only
Chapter 18 - Some Concluding Remarks
Pages 311-313 - Book chapterNo access
References
Pages 315-327 - Book chapterNo access
Index
Pages 329-339
About the book
Description
Written for those who need an introduction, Applied Time Series Analysis reviews applications of the popular econometric analysis technique across disciplines. Carefully balancing accessibility with rigor, it spans economics, finance, economic history, climatology, meteorology, and public health. Terence Mills provides a practical, step-by-step approach that emphasizes core theories and results without becoming bogged down by excessive technical details. Including univariate and multivariate techniques, Applied Time Series Analysis provides data sets and program files that support a broad range of multidisciplinary applications, distinguishing this book from others.
Written for those who need an introduction, Applied Time Series Analysis reviews applications of the popular econometric analysis technique across disciplines. Carefully balancing accessibility with rigor, it spans economics, finance, economic history, climatology, meteorology, and public health. Terence Mills provides a practical, step-by-step approach that emphasizes core theories and results without becoming bogged down by excessive technical details. Including univariate and multivariate techniques, Applied Time Series Analysis provides data sets and program files that support a broad range of multidisciplinary applications, distinguishing this book from others.
Key Features
- Focuses on practical application of time series analysis, using step-by-step techniques and without excessive technical detail
- Supported by copious disciplinary examples, helping readers quickly adapt time series analysis to their area of study
- Covers both univariate and multivariate techniques in one volume
- Provides expert tips on, and helps mitigate common pitfalls of, powerful statistical software including EVIEWS and R
- Written in jargon-free and clear English from a master educator with 30 years+ experience explaining time series to novices
- Accompanied by a microsite with disciplinary data sets and files explaining how to build the calculations used in examples
- Focuses on practical application of time series analysis, using step-by-step techniques and without excessive technical detail
- Supported by copious disciplinary examples, helping readers quickly adapt time series analysis to their area of study
- Covers both univariate and multivariate techniques in one volume
- Provides expert tips on, and helps mitigate common pitfalls of, powerful statistical software including EVIEWS and R
- Written in jargon-free and clear English from a master educator with 30 years+ experience explaining time series to novices
- Accompanied by a microsite with disciplinary data sets and files explaining how to build the calculations used in examples
Details
ISBN
978-0-12-813117-6
Language
English
Published
2019
Copyright
Copyright © 2019 Elsevier Inc. All rights reserved.
Imprint
Academic Press