A parameter estimator achieving the Cramer-Rao lower bound will have an efficiency of 1. [Pg.53]

Finally we need to compare the variance of our estimator with the best attainable. It can be shown that The Cramer-Rao lower bound (CRLB) is a lower bound on the variance of an unbiased estimator (Kay, 1993). The quantities estimated can be fixed parameters with unknown values, random variables or a signal and essentially we are finding the best estimate we can possibly make. [Pg.389]

The essential criteria for a good fit are that the returned parameters should be as accurate as permitted by the data and that the fitting process should be robust. The theoretical limit on the uncertainties of each of the parameters in the model is given by the Cramer Rao lower bound. The Cramer Rao bound applies to any unbiased estimator 0(y) of a parameter vector, 9, using measurements, y. The measurements are described by their joint probability density function p(y 6), which is influenced by 9. [Pg.93]

© 2019 chempedia.info