Bayesian model parameter estimation of systems subject to random input and output measurement error

Author

Perttunen, Cary D.

Author_Institution

Dept. of Electr. Eng., Louisville Univ., KY, USA

fYear

1989

fDate

0-0 1989

Firstpage

227

Lastpage

230

Abstract

A method, based on Bayesian statistics, for estimating the parameters of a general multiple-input single-output model subject to random input and output measurement error of any distributional form is proposed. First, the method for Bayesian parameter estimation is given. An estimate and a probability region for the estimate of the parameters is found. Then, the necessary extensions to allow for a measurement error in the input are formulated. An application of this to the general linear model with measurement error in both the input and output is given. Finally, the parameters of the junction depletion capacitance model of a diode are estimated, and probability regions for these parameters are found.<>

Keywords

Bayes methods; measurement errors; parameter estimation; semiconductor device models; semiconductor diodes; statistical analysis; system theory; Bayesian statistics; diode; junction depletion capacitance model; measurement error; multiple-input single-output model; parameter estimation; Bayes procedures; Measurement errors; Parameter estimation; Semiconductor device modeling; Semiconductor diodes; Statistics;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems Engineering, 1989., IEEE International Conference on

Conference_Location

Fairborn, OH, USA

Type

conf

DOI

10.1109/ICSYSE.1989.48660

Filename

48660