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„It is a suitable text for courses on time series analysisat the (upper) undergraduate and graduate level. It can also serveas a guide for practitioners and researchers who carry out timeseries analysis in engineering, business andeconomics.“ (Zentralblatt MATH, 2012)„Time Series Analysis and Forecasting by Example is wellrecommended as a great introductory book for students transitioningfrom general statistics to time series as well as a good sourcebook for intermediate level time series model builders.“ (BookPleasures, 2012)
„They set out to provide an introduction that is easy tounderstand and use, and that draws heavily from examples todemonstrate the principles and techniques.“ (Book News, 1 October2011)
An intuition-based approach enables you to master time seriesanalysis with ease
Time Series Analysis and Forecasting by Example providesthe fundamental techniques in time series analysis using variousexamples. By introducing necessary theory through examples thatshowcase the discussed topics, the authors successfully helpreaders develop an intuitive understanding of seemingly complicatedtime series models and their implications.
The book presents methodologies for time series analysis in asimplified, example-based approach. Using graphics, the authorsdiscuss each presented example in detail and explain therelevant theory while also focusing on the interpretationof results in data analysis. Following a discussion of whyautocorrelation is often observed when data is collected in time, subsequent chapters explore related topics, including:
* Graphical tools in time seriesanalysis
* Procedures for developing stationary, non-stationary, andseasonal models
* How to choose the best time series model
* Constant term and cancellation of terms in ARIMA models
* Forecasting using transfer function-noise models
The final chapter is dedicated to key topics such as spuriousrelationships, autocorrelation in regression, and multiple timeseries. Throughout the book, real-world examples illustratestep-by-step procedures and instructions using statistical softwarepackages such as SAS®, JMP, Minitab, SCA, and R. A related Website features PowerPoint slides to accompany each chapter as wellas the book's data sets.
With its extensive use of graphics and examples to explain keyconcepts, Time Series Analysis and Forecasting by Example isan excellent book for courses on time series analysis at theupper-undergraduate and graduate levels. it also serves as avaluable resource for practitioners and researchers who carry outdata and time series analysis in the fields of engineering, business, and economics.
Time Series Analysis and Forecasting by Example providesthe fundamental techniques in time series analysis using variousexamples. By introducing necessary theory through examples thatshowcase the discussed topics, the authors successfully helpreaders develop an intuitive understanding of seemingly complicatedtime series models and their implications.
The book presents methodologies for time series analysis in asimplified, example-based approach. Using graphics, the authorsdiscuss each presented example in detail and explain therelevant theory while also focusing on the interpretationof results in data analysis. Following a discussion of whyautocorrelation is often observed when data is collected in time, subsequent chapters explore related topics, including:
* Graphical tools in time seriesanalysis
* Procedures for developing stationary, non-stationary, andseasonal models
* How to choose the best time series model
* Constant term and cancellation of terms in ARIMA models
* Forecasting using transfer function-noise models
The final chapter is dedicated to key topics such as spuriousrelationships, autocorrelation in regression, and multiple timeseries. Throughout the book, real-world examples illustratestep-by-step procedures and instructions using statistical softwarepackages such as SAS®, JMP, Minitab, SCA, and R. A related Website features PowerPoint slides to accompany each chapter as wellas the book's data sets.
With its extensive use of graphics and examples to explain keyconcepts, Time Series Analysis and Forecasting by Example isan excellent book for courses on time series analysis at theupper-undergraduate and graduate levels. it also serves as avaluable resource for practitioners and researchers who carry outdata and time series analysis in the fields of engineering, business, and economics.
