In statistics, an optimality criterion provides a measure of the fit of the data to a given hypothesis. The selection process is determined by the solution that optimizes the criteria used to evaluate the alternative hypotheses. The term has been used to identify the different criteria that are used to evaluate a phylogenetic tree and include maximum likelihood, Bayesian, maximum parsimony, and minimum evolution. For example, in order to determine the best topology between two phylogenetic trees using the maximum likelihood optimality criterion, one would calculate the maximum likelihood score of each tree and choose the one that had the better score. However, different optimality criteria can select different hypotheses. In such circumstances caution should be exercised when making strong conclusions.
Many other disciplines use similar criteria or have specific measures geared toward the objectives of the field.
Famous quotes containing the word criterion:
“There is only one art, whose sole criterion is the power, the authenticity, the revelatory insight, the courage and suggestiveness with which it seeks its truth.... Thus, from the standpoint of the work and its worth it is irrelevant to which political ideas the artist as a citizen claims allegiance, which ideas he would like to serve with his work or whether he holds any such ideas at all.”
—Václav Havel (b. 1936)