Statistical identification of the confidence limits of open loop transfer functions obtained by MAR analysis

Estimators of the confidence limits of open loop transfer functions via Multivariate Auto-Regressive (MAR) modelling are not available in the literature. The statistics of open loop transfer functions obtained by MAR modelling are investigated via numerical experiments. A system of known open loop transfer functions is simulated digitally and excited by random number series. The digital signals of the simulated system are then MAR modelled and the open loop transfer functions are estimated. Performing a large number of realizations, mean values and variances of the open loop transfer functions are estimated. It is found that if the record length N of each realization is long enough then the estimates of open loop transfer functions follow normal distribution. The variance of the open loop transfer functions is proportional to 1/N. For MAR processes the asymptotic covariance matrix of the estimate of open loop transfer functions was found in agreement with theoretical prediction. (author)