Likelihood-ratio test
In statistics, the likelihood-ratio test is a hypothesis test that involves comparing the goodness of fit of two competing statistical models, typically one found by maximization over the entire parameter space and another found after imposing some constraint, based on the ratio of their likelihoods. If the more constrained model (i.e., the null hypothesis) is supported by the observed data, the two likelihoods should not differ by more than sampling error. Thus the likelihood-ratio test tests whether this ratio is significantly different from one, or equivalently whether its natural logarithm is significantly different from zero.
Likelihood-ratio test - Wikipedia Jump to content From Wikipedia, the free encyclopedia Statistical test that compares goodness of fit This article is about the statistical test that compares goodness of fit. For a general description of the likelihood ratio, see Likelihood ratio . For the use of likelihood ratios in interpreting diagnostic tests, see Likelihood ratios in diagnostic testing . In statistics , the likelihood-ratio test is a hypothesis test that involves comparing the goodness of fit of two competing statistical models , typically one found by maximization over the entire paramet
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