Invariance principles and applications to distributed parameter identification

Abstract

A nonlinear least squares parameter estimation procedure is discussed. The main objective is to extend previous results in order to obtain certain functional invariance theorems. In particular, weak convergence methods are used to prove an asymptotic normality result and Strassen's invariance principle is applied to establish a law of the iterated logarithm. Some examples are presented.<>