On regularity conditions for maximum likelihood estimators

Abstract

Summary A theorem by Cramér concerning the asymptotic properties of maximum likelihood estimators is considered here. It is shown that the properties of consistency and asymptotic efficiency can be proved by assuming some uniformity properties of the second order partial derivative of the logarithm of the probability density function. There are no restrictions used in the theorem which require derivatives of higher order than the second.