Ch. 29. Time series in industry and business Book Section


Author(s): Abraham, B.; BALAKRISHNA, N
Editor(s): R. Khattree and C.R. Rao,
Article/Chapter Title: Ch. 29. Time series in industry and business
Book Title: Unknown (0169-7161)
Volume: Volume 22
ISBN: 0169-7161
Publisher: Elsevier  
Date Published: 2003-01-01
Start Page: 1055
End Page: 1106
DOI/URL:
Identifier: 759
Notes: In this chapter we discuss briefly univariate time series analysis with Autoregressive Integrated Moving Average(ARIMA) models. We consider the three-stage model building strategy, the generation of forecasts and several other practical issues such as outliers, missing values and interventions in time series. The application of time series to control problems, state space models and the Kalman filter will also be considered. Non-Gaussian and nonlinear models will be reviewed highlighting some of the more interesting models. We will also consider stochastic volatility models and other models for conditional variances with discussion on ARCH and GARCH models. We will also include a short discussion of long memory (fractional differencing) models.
CUSAT Authors