(-2)*loglikelihood ~ Chi-square?

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I just vaguely remember that I have learned something like "(-2)*loglikelihood asymptotically follows Chi-square distribution."

However, I failed to find the relevant theorems in the textbook. Does anyone know the right theorem for this?

Many thanks!!

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It is called Wilks' theorem. It says that minus twice the logarithm of a maximum likelihood ratio statistic asymptotically approaches the chi-squared distribution as the sample size approaches infinity. Take a look at this.