Under regularity conditions, minus twice the logarithm of a generalized likelihood ratio converges under the null hypothesis to a chi-squared distribution whose degrees of freedom equal the difference in parameter dimensions.
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- Gaussian covariance diagonality likelihood-ratio test
- Individual Bernoulli deviance need not have a chi-squared calibration
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- Upper-endpoint estimation in a truncated distribution
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