Linked from

The 55 pages that link to Maximum likelihood estimation, each with the reason it gives.

• Daniel McFaddenRelated: McFadden used likelihood methods to fit choice models to observed decisions.

• Robert F. EngleRelated: Engle’s conditional-variance models are commonly estimated by maximizing a likelihood function.

• Family (statistics)Related: It estimates which family member best accounts for a sample.

• Gibbs' inequalityRelated: The inequality helps relate expected log-likelihood to the data-generating distribution.

• Sample mean and covarianceCompared with: For a normal model, its covariance estimate uses divisor n, unlike the common unbiased estimate’s n−1.