The parameter estimation problem is formulated for the situation in which the measurement of every variable is subject to noise. The method of maximum likelihood is shown to produce estimators for which the amount of computation is prohibitive but these estimators fire used as a standard against which the accuracy of more easily computed methods may be judged, A number of alternative methods are introduced, a form of weighted least squares being shown to require the least computation and to approximate the accuracy of the maximum likelihood estimators. An example of the appli-cation of this method is given.