On the efficiency of least squares estimators in non-linear models

Summary  The identity of least squares estimators å and maximum likelihood estimators â is studied in non-linear models of the type z = g ( a ), where z are observable quantities with a probability density function pr ( z ). This identity was proved for independent random variables z and for distributions pr ( z ), of which the arithmetic sample mean is an optimal estimate.