Estimating Current Trend and Growth Rates in Seasonal Time Series.
Abstract
The importance of appropriate stochastic models in choosing efficient methods of statistical analysis is discussed. The fitting to data of Seasonal Autoregressive Moving Average models is described and it is shown how trend may be estimated in an appropriate class of models of this kind. The procedure is illustrated for a model fitted to a money supply series published by the Federal Reserve Board. Error limits are calculated. In a series of appendices the properties of the adaptive coefficients which determine the trend estimates are derived. (Author)
Document Details
- Document Type
- Technical Report
- Publication Date
- May 01, 1981
- Accession Number
- ADA100613
Entities
People
- David A. Pierce
- George E. P. Box
Organizations
- University of Wisconsin–Madison