Maximum likelihood

Maximum likelihood estimation (or maximum likelihood) is the name used for a number of ways to guess the parameters of a parametrised statistical model. These methods pick the value of the parameter in such a way that the probability distribution makes the observed values very likely. The method was mainly developed by R.A.Fisher in the early 20th century. A likelihood estimation, where probabilities are known beforehand is known as Maximum a posteriori estimation.

Maximum Likelihood Media

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  A picture showing a function having a global maximum and a horizontal asymptote approaching that maximum as well. Such function will fail when used as an objective for extremum estimation.

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  Likelihood function for proportion value of a binomial process (n = 10)

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  An image of Ronald Fisher in 1913