Applied Bayesian Forecasting and Time Series Analysis
CRC Press
This book is about practical forecasting and analysis of time series. It describes how to analyse time series data, how to identify structure, how to explain observed behaviour, how to model structures and behaviours, and how to use insight gained from the analysis to make informed forecasts. > \nPractical in its approach, Applied Bayesian Forecasting and Time Series Analysis provides the theories, methods, and tools necessary for forecasting and the analysis of time series. The authors unify the concepts, model forms, and modeling requirements within the framework of the dynamic linear mode (DLM). They include a complete theoretical development of the DLM and illustrate each step with analysis of time series data. Using real data sets the authors: Explore diverse aspects of time series, including how to identify, structure, explain observed behavior, model structures and behaviors, and interpret analyses to make informed forecasts Illustrate concepts such as component decompositif
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