Accession Number : AD0641935
Title : DISCRETE MODELS FOR FORECASTING AND CONTROL.
Descriptive Note : Technical rept.,
Corporate Author : WISCONSIN UNIV MADISON DEPT OF STATISTICS
Personal Author(s) : Box,G. E. P. ; Jenkins,G. M.
Report Date : JUN 1966
Pagination or Media Count : 27
Abstract : The authors first describe a class of discrete linear time series models capable of representing nonstationary as well as stationary behavior. In control problems these models are used to describe disturbances to the system. Dynamic models which represent relationships between variables which control and are controlled are later introduced. The identification, fitting, checking and practical use of such models in forecasting and control are discussed. The models employed are empirico-mechanistic in that while they can be interpreted as descriptions of physical phenomena having the right general character they do not claim to represent exact physical reality and are fitted to data empirically. An important principle in the choice of such models is that, they should, while adequately representing the data, contain the fewest possible number of parameters. This is called the principle of parsimony or of parsimonious parametrization. (Author)
Descriptors : (*MATHEMATICAL MODELS, MATHEMATICAL PREDICTION), CONTROL, OPERATIONS RESEARCH
Subject Categories : Operations Research
Distribution Statement : APPROVED FOR PUBLIC RELEASE