Maximum Likelihood Estimators (MLE) that provide population values that maximize the so-called Likelihood Function (LF) that gives the probability of observing the sample data, given the parameter estimates. MLE, therefore, are parameter estimates that maximize the probability of finding the sample data that we have actually found. The MLE are available using the Newton-Raphson Fisher Scoring, Iterative Generalized Least Squares, or the Expectation Maximization algorithms (Longford, 1993).
Computing the MLE requires an iterative procedure.