Forecasting: Methods and Applications
Makridakis, Spyros (2002)
Book chapter
This book covers what the authors call the “full range of major forecasting methods.” These comprise of the traditional time series methods of decomposition, exponential smoothing, simple and multiple linear regression and Box-Jenkins’ ARIMA models. Further to those, this 3rd edition very wisely includes some more advanced forecasting methods such as dynamic regression, neural networks, state space modeling as well as some “new ideas for combining statistical and judgmental forecasting” amongst others. A modern approach to long-term forecasting based on mega trends, analogies and scenarios is also included