Title :
Application of Bayesian statistics and optimization to difference equation parameter estimation
Author :
Perttunen, Cary D. ; Stuckman, Bruce E. ; Laursen, Norman W.
Author_Institution :
Dept. of Electr. Eng., Louisville Univ., KY, USA
Abstract :
The authors present a method for estimating the parameters of a difference equation from data that has random error in both the input and output measurements. A stochastic global optimization technique iteratively determines the set of parameters that maximize the posterior density function for the parameters conditioned upon the error between the measured output data and simulated data derived from the model. Examples show that errors in parameter estimates in the presence of input error can be reduced in comparison with other techniques.<>
Keywords :
Bayes methods; difference equations; optimisation; parameter estimation; stochastic processes; Bayesian statistics; difference equation parameter estimation; posterior density function; random error; stochastic global optimization technique; Bayes procedures; Difference equations; Optimization methods; Parameter estimation; Stochastic processes;
Conference_Titel :
Systems Engineering, 1989., IEEE International Conference on
Conference_Location :
Fairborn, OH, USA
DOI :
10.1109/ICSYSE.1989.48712
