The likelihood ratio test is a statistical method used to compare the fit of two models to a set of data, typically a null hypothesis model against an alternative hypothesis model. It calculates the ratio of the maximum likelihoods of the two models, providing a way to evaluate whether the data provides sufficient evidence to reject the null hypothesis in favor of the alternative. This method is closely linked to maximum likelihood estimation, sufficiency, and Bayesian estimation, as it relies on likelihood functions and can incorporate prior information when evaluating hypotheses.
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