In statistics, local asymptotic normality is a property of a sequence of statistical models, which allows this sequence to be asymptotically approximated by a normal location model, after an appropriate rescaling of the parameter. An important example when the local asymptotic normality holds is in the case of i.i.d sampling from a regular parametric model.
The notion of local asymptotic normality was introduced by Le Cam (1960) and is fundamental in the treatment of estimator and test efficiency.[1]