Applied Time Series Analysis. A Practical Guide to Modeling and Forecasting 1st edition Terence C. Mills

Applied Time Series Analysis. A Practical Guide to Modeling and Forecasting 1st edition Terence C. Mills – Ebook Instant Download/Delivery ISBN(s): 9780128131176,0128131179,9780128131183, 0128131187

Product details:

• ISBN 10:0128131187
• ISBN 13:9780128131183
• Author: Terence C. Mills

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.

Table contents:

Chapter 1. Time Series and Their Features
Chapter 2. Transforming Time Series
Chapter 3. ARMA Models for Stationary Time Series
Chapter 4. ARIMA Models for Nonstationary Time Series
Chapter 5. Unit Roots, Difference and Trend Stationarity, and Fractional Differencing
Chapter 6. Breaking and Nonlinear Trends
Chapter 7. An Introduction to Forecasting With Univariate Models
Chapter 8. Unobserved Component Models, Signal Extraction, and Filters
Chapter 9. Seasonality and Exponential Smoothing
Chapter 10. Volatility and Generalized Autoregressive Conditional Heteroskedastic Processes
Chapter 11. Nonlinear Stochastic Processes
Chapter 12. Transfer Functions and Autoregressive Distributed Lag Modeling
Chapter 13. Vector Autoregressions and Granger Causality
Chapter 14. Error Correction, Spurious Regressions, and Cointegration
Chapter 15. Vector Autoregressions With Integrated Variables, Vector Error Correction Models, and Common Trends
Chapter 16. Compositional and Count Time Series
Chapter 17. State Space Models
Chapter 18. Some Concluding Remarks

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