We supplement the article of Meng (2006) on the EM algorithm and its applications, providing also an update on its more recent developments and applications. The expectation–maximization algorithm, popularly known as the EM algorithm, is a general-purpose algorithm for maximum-likelihood estimation in a wide variety of situations best described as incomplete-data problems. The name EM algorithm was given by Dempster et al. (1997) in a celebrated paper read before the Royal Statistical Society in 1976 and published in its journal in 1977.