Numerical experiments are performed to measure the relative accuracy and computational efficiency of various estimators for the parameters and state of a linear dynamic system with forcing using a finite sequence of measurements containing noise. This nonlinear estimation problem is treated by estimators based on least-squares and maximumlikelihood criteria and, for the linearized problem, two mechanizations of the Kalman-Bucy estimator are applied. A digital computer simulation of an example problem is performed, and a Monte Carlo technique is used to generate statistics of the errors in the estimates empirically. This process is carried out for a range of a priori error statistics. © 1967 Plenum Publishing Corporation.