AbstractThis article addresses different facets of maximum likelihood estimation. Starting with the likelihood function, the Cramér‐Rao inequality and properties of maximum likelihood estimators are described. Another estimator, namely, the conditional mean estimator, is discussed. An iterative algorithm, known as the Expectation‐Maximization (EM) algorithm, for computing the maximum likelihood estimate is described.
