Название: Applied Time Series Analysis: A Practical Guide to Modeling and Forecasting
Автор: Terence C. Mills
Издательство: Academic Press, Elsevier
Год: 2019
Страниц: 337
Язык: английский
Формат: pdf (true), epub
Размер: 16.2 MB

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.

Time series, although ubiquitous, require analysing with special statistical concepts and techniques, for without them erroneous inferences and conclusions may all to easily be drawn. Autocorrelation is the key feature of an individual time series or a group of time series. Related to this measure of “internal correlation” are further features, such as stationarity, nonstationarity, often involving the presence of trends, cycles, and periodic movements, seasonality, and volatility. Time series may also exhibit natural constraints, such as nonnegativity, integer values, and series that are defined as proportions, or compositions, of a whole. All these key features are introduced and discussed using examples of observed time series taken from a variety of fields.

- 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