A commonly used method for obtaining an estimate of an unknown parameter of an assumed population distribution. The likelihood of a data set depends upon the parameter(s) of the distribution (or probability density function) from which the observations have been taken. In cases where one or more of these parameters are unknown, a shrewd choice as an estimate would be the value that maximizes the likelihood. This is the maximum likelihood estimate (mle). Expressions for maximum likelihood estimates are frequently obtained by maximizing the natural logarithm of the likelihood rather than the likelihood itself (the result is the same). Sir Ronald Fisher introduced the method in 1912.
Subjects: Probability and Statistics.