Accession Number : AD0746694

Title :   Statistical Models for Control and Optimization Techniques.

Descriptive Note : Final rept. 1 Jun 69-31 May 72,

Corporate Author : WISCONSIN UNIV MADISON DEPT OF STATISTICS

Personal Author(s) : Box,George E. P. ; Wahba,Grace ; Guttman,Irwin

Report Date : AUG 1972

Pagination or Media Count : 10

Abstract : The main thrust of the research has been to continue the development of univariate and multivariate time series and dynamic model-building techniques. Important problems are associated with estimation of parameters which appear non-linearly. This has been tackled by use of Bayes' methods. Investigations have been made into lagged variable forecasting techniques, behavior of sample autocorrelation functions for non-stationary series, distribution theory of partial autocorrelation functions, new methods for estimation of parameters in non-linear models. The use of Reproducing Kernel Hilbert spaces as a tool to solve optimization problems occurring in continuous time control is being studied extensively. Numerical methods for solving linear operator equations occurring in control problems were developed and established. A numerical method for minimizing a quadratic functional subject to a continuous family of linear inequality constraints was analyzed. (Author)

Descriptors :   (*ADAPTIVE CONTROL SYSTEMS, MATHEMATICAL MODELS), TIME SERIES ANALYSIS, STOCHASTIC PROCESSES, TRANSFER FUNCTIONS, MATHEMATICAL PREDICTION, DISTRIBUTION THEORY, OPTIMIZATION

Subject Categories : Statistics and Probability

Distribution Statement : APPROVED FOR PUBLIC RELEASE