Anatomy of Some Time Series Models.
Abstract
Most naturally occurring data are serial in space or time. With randomized designs, analysis which ignores the serial structure is possible. When the ordering of the data is not at our disposal adequate models must take specific account of serial structure and allow for error dependence, possible non-stationarity, time trend removal, dynamic relationships between variables, feedback between variables, and choice of dependent and independent variables. Stochastic difference equations supply a useful class of serial models. Some aspects of their structure are illustrated with practical examples. (Author)
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 01, 1983
- Accession Number
- ADA130498
Entities
People
- George E. P. Box
Organizations
- University of Wisconsin–Madison